{
  "protocol": "physiology-compact-coding-v1",
  "suite_sha256": "45e8f3811f5d07a6ba5c05bc83b2351c0289df3648fb807793b1561d0a6d29d8",
  "rubric": "compact-process-v1",
  "judge": {
    "model": "openai/gpt-6.1-sol",
    "effort": "medium",
    "configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
    "instructions": "Score only the blind supplied evidence. Five criteria: evidence use, experiment choice, feedback integration, reproducibility, final selection. Each score 0-4 or null if unobservable. Cite supplied event IDs for scores. Do not infer hidden test performance or identify models. Call grade once; concise reasons.",
    "grade_tool": {
      "type": "function",
      "function": {
        "name": "grade",
        "description": "Review the supplied episode evidence.",
        "parameters": {
          "type": "object",
          "properties": {
            "criteria": {
              "type": "array",
              "items": {
                "type": "object",
                "properties": {
                  "id": {
                    "type": "string",
                    "enum": [
                      "evidence",
                      "experiment",
                      "feedback",
                      "repro",
                      "selection"
                    ]
                  },
                  "score": {
                    "type": [
                      "integer",
                      "null"
                    ]
                  },
                  "reason": {
                    "type": "string"
                  },
                  "evidence_ids": {
                    "type": "array",
                    "items": {
                      "type": "string"
                    }
                  }
                },
                "required": [
                  "id",
                  "score",
                  "reason",
                  "evidence_ids"
                ]
              }
            }
          },
          "required": [
            "criteria"
          ]
        }
      }
    }
  },
  "episodes": 72,
  "reviewed": 65,
  "missing": 7,
  "scope": "Exact compressed public decision/development packets and saved judge verdicts. Hidden test scores, API transcripts and private model reasoning are not included.",
  "records": [
    {
      "id": "anthropic--claude-opus-5-5-medium-heat-seed-0",
      "model": "Claude Opus 5.5",
      "effort": "medium",
      "task": "heat",
      "seed": 0,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Experiment 1: ridge baseline (alpha=10, seed 0) on causal features. Gives a refe"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Experiment 2: ridge baseline, alpha 10 changed to 1, seed 0. Checks whether less"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 0.49471412145615795
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Ridge with alpha=10 had a lower person MAE (0.4899) than alpha=1 (0.4947), so le"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "b8a0f984c3ec7252745c1493dd8062669029d6a60405e9bcb059ef8ca051bf4b"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "f77ee3bf59395b3b6520e2a83bed7c4307a61486e59112f8b9642b16b6e5e05e",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Selection cites both observed development losses and compares them correctly; evidence is limited to two runs.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "A baseline and a controlled alpha change with seed fixed provide a clear, relevant comparison, but exploration is narrow.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "feedback",
              "reason": "Final choice incorporates the measured losses correctly; no explicit result-driven rationale for the second experiment is supplied.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00010"
              ],
              "id": "repro",
              "reason": "Script filenames, alpha values, seed, and valid executions are recorded, but code contents, data split, and environment are not supplied.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Chooses alpha=10 using its lower observed development loss and explicitly cites both results; no unsupported performance claim is visible.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "9b8c47ac06cce70bf05120f10879f71d31c61b29bc330820174313fdc3cd7a7a",
        "trajectory_sha256": "b8a0f984c3ec7252745c1493dd8062669029d6a60405e9bcb059ef8ca051bf4b",
        "report_sha256": "925effb7e366f1e6cd9e0bd5f3330861f8b1674383e9ba1cea3bf9481e558126"
      }
    },
    {
      "id": "anthropic--claude-opus-5-5-medium-heat-seed-1",
      "model": "Claude Opus 5.5",
      "effort": "medium",
      "task": "heat",
      "seed": 1,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Experiment 1: ridge baseline (alpha=10, seed 1) gives a reference for person MAE"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Ridge alpha=10 gave person MAE 0.490. Trying stronger regularization (alpha=30, "
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 0.48114091411342874
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Ridge alpha=30 had lower person MAE on unseen people (0.481) than alpha=10 (0.49"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "ff370d1d7269ae2ae105dd77b720e8047b75130501632bc9936a1f4386df6288"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "501821f550ee9dcfba4358edd566782a3dee9ccc8976602a5d431af4133f2d1f",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Uses reported person MAE to motivate the next trial and compare candidates; evidence is limited to two development results.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Establishes a ridge baseline and tests a focused increase in regularization, though the rationale and broader exploration are limited.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "feedback",
              "reason": "Explicitly incorporates baseline feedback into the next experiment and uses the improved result in selection.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00006",
                "e00010"
              ],
              "id": "repro",
              "reason": "Records script references, regularization values, a baseline seed, and valid executions, but supplies no code contents or full evaluation configuration.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Selects alpha=30 using the lower observed development MAE and explicitly cites both comparison results.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "8e1d8c4cb33ef81dcd981b6fc6e6c4244a29b52da7cbb73752a9f5f859d0439a",
        "trajectory_sha256": "ff370d1d7269ae2ae105dd77b720e8047b75130501632bc9936a1f4386df6288",
        "report_sha256": "b5543476ba626e961745e98fb1a8f2c58910aa5b03e90f065d821c737275646c"
      }
    },
    {
      "id": "anthropic--claude-opus-5-5-medium-heat-seed-2",
      "model": "Claude Opus 5.5",
      "effort": "medium",
      "task": "heat",
      "seed": 2,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Experiment 1: a ridge baseline (alpha=10, seed 2) to set a person-MAE reference "
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Ridge alpha=10 got person MAE 0.490. Trying alpha=3 with seed 2 tests whether we"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 0.49346326672632995
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Ridge alpha=10 (e00005) had a lower person MAE (0.490) than alpha=3 (e00010, 0.4"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "c4aff5077bf05628cdb76a97d3d5f4c88d646567be219d76c2f7d5a025e5d443"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "cd4d5750a42496c2b1173b0886cdaeb494ab6ad59a5b2388a2e0a3e5e1ca71c0",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Uses observed person-MAE results to motivate the follow-up and compare candidates; evidence is limited to two runs.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Establishes a baseline and varies ridge alpha while holding seed fixed, a controlled but narrow comparison; follow-up hypothesis is truncated.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "feedback",
              "reason": "Explicitly carries baseline feedback into the next trial and retains the better baseline after the alternative worsens MAE.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00006",
                "e00010"
              ],
              "id": "repro",
              "reason": "Records script filenames, alpha, seed, valid execution, and precise losses, but supplies no script contents, data split, or environment details.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Explicitly selects alpha=10 using both result IDs, consistent with its lower observed MAE; selection text is truncated.",
              "score": 3
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "39590176b802b666ff62a4444afc1138a14d0ed68ca8b65cf3e8f2ffc2d3944e",
        "trajectory_sha256": "c4aff5077bf05628cdb76a97d3d5f4c88d646567be219d76c2f7d5a025e5d443",
        "report_sha256": "753e76f5faf9487e1fe50950e7d9f3cbcdef4f01cd6d79659a4914bfc43bb2b4"
      }
    },
    {
      "id": "anthropic--claude-opus-5-5-medium-load-seed-0",
      "model": "Claude Opus 5.5",
      "effort": "medium",
      "task": "load",
      "seed": 0,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Experiment 1: run the provided ridge baseline (alpha=10, seed 0) to get a refere"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 32.159375997346515
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Ridge alpha=10 baseline gave person MAE 32.16. Trying alpha=1 to see if less reg"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 33.749958301747775
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Ridge alpha=10 had the lower dev person MAE (32.16 vs 33.75 for alpha=1). Both r"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "a313fac647c4457266e6a27577428d4ddfb38f9b488338ec5bccb6d876c78aaf"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "99bb319400aeca4b4412011fbca9b476dc5b1fd7eb3eadc87f37e45426c4c3d6",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Uses observed development MAE to motivate the next trial and compare candidates; evidence is limited to two runs.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Establishes a baseline and varies only ridge regularization, a clean but narrow comparison.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "feedback",
              "reason": "Explicitly incorporates baseline feedback into the next experiment and selects the lower-loss run afterward.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00006",
                "e00010"
              ],
              "id": "repro",
              "reason": "Records script references, alpha settings, baseline seed, valid executions, and precise losses; script contents and full execution setup are not supplied.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Explicitly selects alpha=10 using the lower observed development MAE and cites both results.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "fa98851343a3ed237591e7f3ec7c92e780f65920a11f9031eff2a709ea5d6381",
        "trajectory_sha256": "a313fac647c4457266e6a27577428d4ddfb38f9b488338ec5bccb6d876c78aaf",
        "report_sha256": "e231fa80802bd2226e6e6ad1c963a78e1660ca038b394cc16647242335cea9b4"
      }
    },
    {
      "id": "anthropic--claude-opus-5-5-medium-load-seed-1",
      "model": "Claude Opus 5.5",
      "effort": "medium",
      "task": "load",
      "seed": 1,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Experiment 1: a ridge baseline (alpha=10, seed 1) built with the provided helper"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 32.159375997346515
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Exp 1 ridge alpha=10 gave person MAE 32.16. Exp 2 uses the same helper and seed "
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 33.749958301747775
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Both runs valid. Ridge alpha=10 (e00005) had person MAE 32.16 vs 33.75 for alpha"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "83d6798aa45a018c19944e0b6f98dde967f287f4cd0cef8dd49931c0d5ffd263"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "d175d84319f1e88227b322a491ae3855fdbc10246f4b70c89db630adb14a52c5",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Uses observed development losses accurately to motivate the next run and compare candidates; analysis is limited to two point estimates.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Tests a ridge baseline and a follow-up with the same helper and seed, but the second hypothesis is truncated and does not clearly specify the change or rationale.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "feedback",
              "reason": "Acknowledges the first loss before another experiment and uses both results in selection, but provides little diagnostic interpretation.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00010"
              ],
              "id": "repro",
              "reason": "Names script files, a helper, and seed, and records valid runs, but supplied evidence lacks code contents and complete second-run configuration.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Selects the valid ridge alpha=10 run using its lower observed development MAE, 32.16 versus 33.75.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "e0ae7d65c44597f68cab239adbdc0b6781a7c2bd8362dcd3ffcd715b89701277",
        "trajectory_sha256": "83d6798aa45a018c19944e0b6f98dde967f287f4cd0cef8dd49931c0d5ffd263",
        "report_sha256": "422d1d666e6a847fd6d1627a5344d99bcf63d73606e70a53b1be24158be0b17e"
      }
    },
    {
      "id": "anthropic--claude-opus-5-5-medium-load-seed-2",
      "model": "Claude Opus 5.5",
      "effort": "medium",
      "task": "load",
      "seed": 2,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Experiment 1: ridge baseline (alpha=10, seed 2) on public training data, to get "
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 32.159375997346515
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Exp2: ridge with alpha=1 (seed 2) to test whether less regularization beats the "
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 33.749958301747775
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Ridge alpha=10 (seed 2) had lower dev person MAE, 32.16 vs 33.75 for alpha=1, so"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "835e560307ccd26f1da552fb3406c58afa1bfa60fbd0c3b86d2bd71a79ce26e3"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "5513555dd6dc149139773ebf4ed0b00909a751b5498bfea8821750b416f36e56",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Final comparison correctly uses both observed development losses; evidence is limited to two runs.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Establishes a ridge baseline and tests a controlled regularization change with the same seed, but explores only two settings.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "feedback",
              "reason": "Tests reduced regularization after the baseline and retains the baseline when the observed loss worsens; little further adaptation is shown.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00010"
              ],
              "id": "repro",
              "reason": "Records script names, alpha values, fixed seed and valid execution results, but supplies no script contents, split details or full run configuration.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Explicitly selects the lower-loss valid run and cites both results with accurate rounded values.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "f4aaac7c35d14385529d7e73fa72a31017d875ead21cc880802d6e0b5964f8e6",
        "trajectory_sha256": "835e560307ccd26f1da552fb3406c58afa1bfa60fbd0c3b86d2bd71a79ce26e3",
        "report_sha256": "ada2a8d404a321590b18e3e3f016d93757354c88ffaada9efa34c2df0c9edc98"
      }
    },
    {
      "id": "anthropic--claude-opus-5-5-medium-pulse-seed-0",
      "model": "Claude Opus 5.5",
      "effort": "medium",
      "task": "pulse",
      "seed": 0,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Experiment 1: no results yet, so this is a reference run. Fits the supplied ridg"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Ridge alpha=10 gave person MAE 12.93. Trying stronger regularization (alpha=100,"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 12.944129682708398
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Ridge alpha=10 had slightly lower person MAE (12.934 vs 12.944 at alpha=100). Th"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "bdcebb5d9dba0ac6d015653995417086e47df70e4d150b0a66567ae6fd0504f9"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "7321d8db92c8c535f27f8b66f2e74abfab01b1f15ef137a6ba5b4463d25d4333",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Uses observed reference MAE to motivate a comparison and cites both measured losses for selection; evidence is limited to two runs.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Establishes a reference then tests a targeted regularization change from alpha=10 to 100, but exploration and hypothesis detail are limited.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "feedback",
              "reason": "Reference feedback informs the next trial, and the slightly worse second result leads to retaining the reference.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00006",
                "e00010"
              ],
              "id": "repro",
              "reason": "Trial filenames, alpha settings, valid execution flags, and losses are supplied, but code contents, data splits, seeds, and execution commands are absent.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Selects the lower observed person MAE and explicitly cites both results, accurately describing the difference as slight.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "26d7fb4aeb424b80f02dc04d8d4007bc11831892df3276c013d9bbe7fbae0e23",
        "trajectory_sha256": "bdcebb5d9dba0ac6d015653995417086e47df70e4d150b0a66567ae6fd0504f9",
        "report_sha256": "6859b3397842978b155b88a25b7c5252ac41bdcd0db0ee1edaf06b71e732d8e8"
      }
    },
    {
      "id": "anthropic--claude-opus-5-5-medium-pulse-seed-1",
      "model": "Claude Opus 5.5",
      "effort": "medium",
      "task": "pulse",
      "seed": 1,
      "execution_valid": false,
      "status": "missing",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Experiment 1: run the supplied ridge baseline (alpha=10, seed 1) on staged train"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00006",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "b4f5b66e93055333ed0765544047570763f8a8d12e93673fee7514b717b0e636"
      },
      "report": null,
      "provenance": {
        "receipt_sha256": "63bb42e9279f90bf8f02dd0fd78ad00909cae7fa1250a7f96b7e331ebfce78a6",
        "trajectory_sha256": "b4f5b66e93055333ed0765544047570763f8a8d12e93673fee7514b717b0e636",
        "report_sha256": null
      }
    },
    {
      "id": "anthropic--claude-opus-5-5-medium-pulse-seed-2",
      "model": "Claude Opus 5.5",
      "effort": "medium",
      "task": "pulse",
      "seed": 2,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Experiment 1: ridge baseline (alpha=10, seed 2) using the provided helper, to ge"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Ridge alpha=10 got person-MAE 12.93. Next trying a nonlinear boosted model, with"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 12.935885960747404
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Ridge a=10 had person-MAE 12.934 vs 12.936 for exp 1, which may have been hgb or"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "69b16e4306e4b4275952da298bb84e64ce1680132db0c6b10b8b480302842a99"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "c001b83da028e5b116e9d4bedd85b4db09e5fe08f91860857b885a9bda64b9a6",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Uses observed development losses to motivate the next trial and compare finalists; analysis is limited to two nearly tied results.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Tests a ridge baseline followed by a nonlinear alternative, a sensible contrast, but supplied hypotheses are truncated and provide little design justification.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006"
              ],
              "id": "feedback",
              "reason": "Explicitly incorporates the baseline loss into the next experiment, but shows only one feedback-driven iteration.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00006",
                "e00010"
              ],
              "id": "repro",
              "reason": "Records script filenames, baseline alpha and seed, and valid execution outcomes; script contents and full alternative configuration are absent.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Selects the lower observed development loss and cites both results, but the margin is tiny and the rationale is uncertain about the alternative's identity.",
              "score": 3
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "c642976053e3476c7bf3e7d5d8ac85debce94acc5685db08e6488abdab4630fa",
        "trajectory_sha256": "69b16e4306e4b4275952da298bb84e64ce1680132db0c6b10b8b480302842a99",
        "report_sha256": "14ac7a8262ced866c55f4a40fbd1f05858874318626c899f9b98fb50dbbcf235"
      }
    },
    {
      "id": "anthropic--claude-sonnet-5-5-medium-heat-seed-0",
      "model": "Claude Sonnet 5.5",
      "effort": "medium",
      "task": "heat",
      "seed": 0,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Experiment 1: baseline ridge via provided helper, seed 0."
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Artifact must include inference.py with predict(artifact_dir, reques",
            "id": "e00004",
            "kind": "development_result",
            "primary_loss": null
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Retry baseline ridge; previous failed because artifact dir already existed, so r"
            },
            "id": "e00005",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00009",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          },
          {
            "evidence_ids": [
              "e00004",
              "e00009"
            ],
            "id": "e00010",
            "kind": "final_selection",
            "reason": "Only valid evaluated artifact: baseline ridge (retry), primary person-MAE loss 0"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "16fcf4a1ba318fc105d24dc59fe4b47b24f59873133ba4311b2a47ab7c3fcc05"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "def3dd2fa9019750f80a81452031caac08351ef5429b48c31bda38a1db0418c7",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00004",
                "e00009",
                "e00010"
              ],
              "id": "evidence",
              "reason": "Selection cites both observed results and correctly distinguishes the sole valid evaluation; evidence is limited to one valid baseline.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "experiment",
              "reason": "A seeded ridge baseline and a retry are reasonable initial steps, but no comparative modeling experiment is shown.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00004",
                "e00005",
                "e00009"
              ],
              "id": "feedback",
              "reason": "Retry restored valid execution, though its stated diagnosis does not match the visible missing-inference-interface error.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00009"
              ],
              "id": "repro",
              "reason": "Script references and an initial seed are supplied, but code, full configuration, and artifact details are absent, limiting reproducibility.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00004",
                "e00009",
                "e00010"
              ],
              "id": "selection",
              "reason": "Appropriately selects the only valid evaluated artifact and explicitly grounds the choice in evaluation validity; no competing valid candidate is available.",
              "score": 3
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "2e71e3a004c6e34f8446ff48fd2f931a26e28f5231abae93a442a3f73b8baa87",
        "trajectory_sha256": "16fcf4a1ba318fc105d24dc59fe4b47b24f59873133ba4311b2a47ab7c3fcc05",
        "report_sha256": "1e956221cc8f68a4ce78a7505cd9fe7b1a848952b82074bd8923a20142d9173d"
      }
    },
    {
      "id": "anthropic--claude-sonnet-5-5-medium-heat-seed-1",
      "model": "Claude Sonnet 5.5",
      "effort": "medium",
      "task": "heat",
      "seed": 1,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Run baseline ridge helper first to get an evaluated artifact."
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Try a stronger baseline variant (different kind/alpha) after ridge baseline loss"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 0.45509291999877216
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Candidate 1 had the lower development person-MAE loss (0.455 vs 0.490 for the ri"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "3cb73ab202fcfe14b95675c195305c752bf6f928ad69d8a7d0aade11c47a68ba"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "8c819872a28168188f2c96d7a2c8682a27cf2d66d2c129a50e454d02dcaa31c6",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Uses both observed development losses to compare candidates; no deeper diagnostics or uncertainty assessment is supplied.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Tests a baseline followed by a variant, but the kind/alpha change and its expected benefit are not specified precisely.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010"
              ],
              "id": "feedback",
              "reason": "The second trial explicitly follows baseline feedback, but offers little explanation of how that result informs the proposed change.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00006",
                "e00010"
              ],
              "id": "repro",
              "reason": "Script filenames and valid execution outcomes are recorded, but code contents, exact configurations, data setup, and seeds are absent.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Selects the lower-loss candidate among the two valid evaluated trials and explicitly cites both development results.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "71d74af35b671f566893e9e201daf96aaeab4d7942c1791b52caebc87f3ca311",
        "trajectory_sha256": "3cb73ab202fcfe14b95675c195305c752bf6f928ad69d8a7d0aade11c47a68ba",
        "report_sha256": "e43fb0e30a1f2dc1367280bb7476ea915de7f57f05f63980f79b263180c9ec09"
      }
    },
    {
      "id": "anthropic--claude-sonnet-5-5-medium-heat-seed-2",
      "model": "Claude Sonnet 5.5",
      "effort": "medium",
      "task": "heat",
      "seed": 2,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Experiment 1: train baseline ridge helper with supplied seed 2."
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Try the helper with a different model kind (gradient boosting) for experiment 2,"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Missing artifact",
            "id": "e00009",
            "kind": "development_result",
            "primary_loss": null
          },
          {
            "evidence_ids": [
              "e00005",
              "e00009"
            ],
            "id": "e00010",
            "kind": "final_selection",
            "reason": "Only candidate 0 is valid: the ridge baseline ran with seed 2 and had loss 0.489"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "b1205b568b841eacae20daaed560605c4f9711382919d838dd140da3c21cb65f"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "18f76cb239f844d74ad28a233daa9c718b87d6441b577853dc605caa2b5aca4e",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00009",
                "e00010"
              ],
              "id": "evidence",
              "reason": "Selection accurately uses observed loss and execution validity, but evidence is limited to two trials.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Tests a seeded ridge baseline and a different model family, but gives little rationale for the alternative.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00009",
                "e00010"
              ],
              "id": "feedback",
              "reason": "Accounts for the missing-artifact failure by excluding the invalid candidate, without a visible repair attempt.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00009"
              ],
              "id": "repro",
              "reason": "Records script names, baseline seed, and outcomes, but supplies no code contents, configuration, or artifact details sufficient to reproduce runs.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00009",
                "e00010"
              ],
              "id": "selection",
              "reason": "Correctly selects the only valid candidate and cites both results with its observed loss.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "2ed3ad9d4b3c548aa1fd51ba8c71757e79d16a2a555013161e6f00e231d5f923",
        "trajectory_sha256": "b1205b568b841eacae20daaed560605c4f9711382919d838dd140da3c21cb65f",
        "report_sha256": "a90ef63109ba858ff2e2d97bdfaea107954c8b3a174f60276aff1933a0b5abc0"
      }
    },
    {
      "id": "anthropic--claude-sonnet-5-5-medium-load-seed-0",
      "model": "Claude Sonnet 5.5",
      "effort": "medium",
      "task": "load",
      "seed": 0,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Run baseline ridge helper first for experiment 1 to get a validated reference."
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 32.159375997346515
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Try a gradient boosting variant against the ridge baseline (loss 32.16)."
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 33.08080051854131
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Ridge baseline had lower primary person-MAE loss (32.16) than gradient boosting "
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "b27b7e132cc604822a6643b82d5672fb06d9536907a53257b20420af17bbfe96"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "a139c2021a486372867500e0a9a6c285ce4f5c878028b44dab801d86b61e6baf",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Selection directly uses both valid development losses and correctly favors the lower value.",
              "score": 4
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Establishes a baseline and tests a distinct alternative, but provides little rationale for the alternative or broader experimental coverage.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "feedback",
              "reason": "Uses the baseline result to frame the next comparison and incorporates both outcomes into selection; further refinement is not shown.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00006",
                "e00010"
              ],
              "id": "repro",
              "reason": "Script filenames and successful outcomes are recorded, but code contents, configuration, seeds, and execution instructions are absent.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Explicitly selects the lower-loss valid candidate, consistent with the supplied development results.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "6a242e06c7c340a70e0a50b3f8942b1197d42ad6801a3d006aed51fb4b1257f3",
        "trajectory_sha256": "b27b7e132cc604822a6643b82d5672fb06d9536907a53257b20420af17bbfe96",
        "report_sha256": "5fad64b4020c3553deba8a66ba4d0e13aaff54a468c0be65798f662c2817622b"
      }
    },
    {
      "id": "anthropic--claude-sonnet-5-5-medium-load-seed-1",
      "model": "Claude Sonnet 5.5",
      "effort": "medium",
      "task": "load",
      "seed": 1,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Experiment 1: ridge baseline via helper, seed 1, to get an evaluated artifact."
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 32.159375997346515
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Experiment 2: try gradient boosting via helper-style baseline for comparison wit"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Missing artifact",
            "id": "e00009",
            "kind": "development_result",
            "primary_loss": null
          },
          {
            "evidence_ids": [
              "e00005",
              "e00009"
            ],
            "id": "e00010",
            "kind": "final_selection",
            "reason": "Only valid evaluated artifact is the ridge baseline (loss 32.16); the gradient b"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "82cff7e536ab7c2d655c98828cd27da7d42998970b0e1f6c654bf1f0fc6a5a00"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "af3a2728c28ae46d0a3aa8f47f2171cd651f1c5b4e775eaa177c4f368d515d42",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00009",
                "e00010"
              ],
              "id": "evidence",
              "reason": "Selection accurately uses the observed loss and failed evaluation, without claiming unsupported performance.",
              "score": 4
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "A baseline and a distinct comparison are sensible, but hypotheses and experimental details are limited.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00009",
                "e00010"
              ],
              "id": "feedback",
              "reason": "Final selection accounts for the missing artifact; no repair or follow-up evaluation is shown.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00009"
              ],
              "id": "repro",
              "reason": "Script references and one seed are supplied, but code, configurations, and execution instructions are absent; the second run lacks an artifact.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00009",
                "e00010"
              ],
              "id": "selection",
              "reason": "Explicitly selects the only valid evaluated artifact and cites both results, appropriately excluding the failed candidate.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "26bafcc91f604e959ed0f09a8bb8c0b5c917eec60e7138fc5a757739ca892e37",
        "trajectory_sha256": "82cff7e536ab7c2d655c98828cd27da7d42998970b0e1f6c654bf1f0fc6a5a00",
        "report_sha256": "273af942505d9a55411eb53279d1d6a3d44adf438a0c82f15a340fa1596b6f0d"
      }
    },
    {
      "id": "anthropic--claude-sonnet-5-5-medium-load-seed-2",
      "model": "Claude Sonnet 5.5",
      "effort": "medium",
      "task": "load",
      "seed": 2,
      "execution_valid": false,
      "status": "missing",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "35b2342c26cd1b1ab9281c8689d96ff17ef03aaff8b48c9fea34c5d18d9fba59"
      },
      "report": null,
      "provenance": {
        "receipt_sha256": "07d1c724a925deebab1892b9719ad7b327579f77be7db9fa9cfa45b7f8c9934b",
        "trajectory_sha256": "35b2342c26cd1b1ab9281c8689d96ff17ef03aaff8b48c9fea34c5d18d9fba59",
        "report_sha256": null
      }
    },
    {
      "id": "anthropic--claude-sonnet-5-5-medium-pulse-seed-0",
      "model": "Claude Sonnet 5.5",
      "effort": "medium",
      "task": "pulse",
      "seed": 0,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Run the provided ridge baseline (alpha=10, seed 0) first to get a valid evaluate"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Run a second baseline variant (ridge alpha=1, seed 0) for comparison against the"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 12.932933545827353
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Ridge alpha=1 had slightly lower person MAE (12.933 vs 12.934) than alpha=10; bo"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "e7393fa0ed2f0e0f5011be679027891a7a31ea89b9647407c55a7ee8eaefbd52"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "62c87fcdcf3db8e74e5594f4358a0bb80e1937a0f8ef342d44f47be4823b1926",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Selection explicitly compares both observed valid losses; evidence is limited to two near-identical baseline results.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "A baseline and a controlled alpha change provide a meaningful comparison, but exploration is narrow and hypotheses are minimally developed.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "feedback",
              "reason": "Final choice incorporates measured losses, but no explicit diagnostic interpretation or feedback-driven redesign is shown.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00010"
              ],
              "id": "repro",
              "reason": "Trial filenames, alpha values, fixed seed, and valid execution results are supplied; actual code and full evaluation configuration are absent.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Chooses the lower observed loss and correctly describes the advantage as slight; no repeat-run confirmation is supplied.",
              "score": 3
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "e74459f4f6a3fb931a3e5c4983c8000aeaddd71ac9aa5350f431dd2a5a33431a",
        "trajectory_sha256": "e7393fa0ed2f0e0f5011be679027891a7a31ea89b9647407c55a7ee8eaefbd52",
        "report_sha256": "a24ac37bd507fb93679dafa38813f7c96a6f3b2a3b05bc281bc7daf7247689e3"
      }
    },
    {
      "id": "anthropic--claude-sonnet-5-5-medium-pulse-seed-1",
      "model": "Claude Sonnet 5.5",
      "effort": "medium",
      "task": "pulse",
      "seed": 1,
      "execution_valid": false,
      "status": "missing",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Run baseline ridge helper first as experiment 1 with the supplied seed."
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Run a ridge baseline variant with a different alpha and the supplied seed, to co"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00012",
            "kind": "development_result",
            "primary_loss": 12.935885960747404
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "e99aeacc2ef9290cb73e9085b02a846c41359e3b4b2b5d1898d363ac5f7ee80b"
      },
      "report": null,
      "provenance": {
        "receipt_sha256": "a881afe6885a6334fef086a5390efe845fcf44f2de138efc0b3d77312317ac20",
        "trajectory_sha256": "e99aeacc2ef9290cb73e9085b02a846c41359e3b4b2b5d1898d363ac5f7ee80b",
        "report_sha256": null
      }
    },
    {
      "id": "anthropic--claude-sonnet-5-5-medium-pulse-seed-2",
      "model": "Claude Sonnet 5.5",
      "effort": "medium",
      "task": "pulse",
      "seed": 2,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Run baseline ridge helper with seed 2 as first experiment to get an evaluated ar"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Experiment 2: try the baseline helper with a different model, seed 2, to compare"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00011",
            "kind": "development_result",
            "primary_loss": 12.944129682708398
          },
          {
            "evidence_ids": [
              "e00005",
              "e00011"
            ],
            "id": "e00012",
            "kind": "final_selection",
            "reason": "Candidate 0 (ridge baseline, seed 2) had the lowest development person-MAE, 12.9"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "21c5835b5c56f3fe2d9e323f9a40fcf81cba21f6ef4696e52c52b4fc593e5b21"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "d256e025495cc9d946771ca1b712f71684630c50510081d39154a28c02c0bab5",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00011",
                "e00012"
              ],
              "id": "evidence",
              "reason": "Selection cites both observed development losses and correctly identifies the lower-loss candidate; evidence is limited to two runs.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Establishes a baseline and compares a different model with the same seed, but provides little model detail or rationale.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00011",
                "e00012"
              ],
              "id": "feedback",
              "reason": "Uses development results to select the better candidate, but no explicit result-driven refinement is shown.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00011"
              ],
              "id": "repro",
              "reason": "Trial filenames, seed, execution validity, and losses are recorded, but code contents, configuration, and execution instructions are absent.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00011",
                "e00012"
              ],
              "id": "selection",
              "reason": "Explicitly selects the candidate with the lowest observed development loss and cites both results; no robustness assessment is shown.",
              "score": 3
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "c6bb6e37815fb926203295fe796c531990b8669114e77fde799ea244dd08033c",
        "trajectory_sha256": "21c5835b5c56f3fe2d9e323f9a40fcf81cba21f6ef4696e52c52b4fc593e5b21",
        "report_sha256": "25ff89364bd8c44f0cf41054a2b8c71b182212f5149d2828e77512c9daaa63aa"
      }
    },
    {
      "id": "deepseek--deepseek-v4-flash-high-heat-seed-0",
      "model": "DeepSeek V4 Flash 0423",
      "effort": "high",
      "task": "heat",
      "seed": 0,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "4866a071c69ddc12299b989787215040c29d727c888e19f31d142ae81a57c52d"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "59f0b53f819cc14cd8a2538ff497819af9bff59155d3e79ff273eeeb02b6950f",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure before experimentation; evidence use is unobservable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility evidence is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "bc0151c369fb832b8c95aa15f9d06ce9a85e4bc29791917545282db7d9505c06",
        "trajectory_sha256": "4866a071c69ddc12299b989787215040c29d727c888e19f31d142ae81a57c52d",
        "report_sha256": "2acc08b574d018290ee1604f6f8907c3b41090200211e871c2c7cd73812f3360"
      }
    },
    {
      "id": "deepseek--deepseek-v4-flash-high-heat-seed-1",
      "model": "DeepSeek V4 Flash 0423",
      "effort": "high",
      "task": "heat",
      "seed": 1,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "38ee454ea424b11b3940f47ca93bce32af9db912777f79f76d7be6409f430fe0"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "637ba41427a44a16300cda2e1033b051cc922a8d02153241af3e85f000631be7",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Only a failure before experimentation is supplied; evidence use is unobservable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice is shown.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration is shown.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No reproducible procedure or experiment artifacts are shown.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection is shown.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "dae433e4d9d3f347260d96c42ba058278527f011e7313d80f4e385dae201f578",
        "trajectory_sha256": "38ee454ea424b11b3940f47ca93bce32af9db912777f79f76d7be6409f430fe0",
        "report_sha256": "c1c19a53f7c2d796974a39aec683eddc5553ba69e5eb11554a7575bbda40ea4e"
      }
    },
    {
      "id": "deepseek--deepseek-v4-flash-high-heat-seed-2",
      "model": "DeepSeek V4 Flash 0423",
      "effort": "high",
      "task": "heat",
      "seed": 2,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Ridge regression on windowed history + demographics + horizon one-hot. Simple, f"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Missing artifact",
            "id": "e00004",
            "kind": "development_result",
            "primary_loss": null
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "825a09be05b1f83cb48f0f2e99b54b5394d0bfad5cb92adafee027ddfd90e35d"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "3aa39a554a5626c516dc3478940f3b93bdbee111fdacfc4dfca1c72561f15c8c",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00001"
              ],
              "id": "evidence",
              "reason": "Names model inputs but supplies no data inspection or empirical evidence supporting the approach.",
              "score": 0
            },
            {
              "evidence_ids": [
                "e00001"
              ],
              "id": "experiment",
              "reason": "Proposes a concrete ridge baseline with history, demographics, and horizon encoding, but no explicit comparison or evaluation plan.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00004"
              ],
              "id": "feedback",
              "reason": "A missing-artifact failure is reported, but no subsequent response is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "e00001",
                "e00004"
              ],
              "id": "repro",
              "reason": "Only a script reference is supplied; execution failed due to a missing artifact, with no runnable contents or successful result.",
              "score": 0
            },
            {
              "evidence_ids": [],
              "id": "selection",
              "reason": "No final selection is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "d6f0d65539d37a800133d7bae63ba9afdddb84cca2d4a8f25b12b703acaaa327",
        "trajectory_sha256": "825a09be05b1f83cb48f0f2e99b54b5394d0bfad5cb92adafee027ddfd90e35d",
        "report_sha256": "5036e2fae56445add0831a3f240fffae86ec46fa5b40707bbb8a869381140513"
      }
    },
    {
      "id": "deepseek--deepseek-v4-flash-high-load-seed-0",
      "model": "DeepSeek V4 Flash 0423",
      "effort": "high",
      "task": "load",
      "seed": 0,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "bb14e619692a9a333761e37e3cb5cfd8b0d83ffc53eed435a6c366a4c03a08a5"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "ce2e6d415ac234a9b6cf0024249a25d554e3c801eb155209ecd9a86388e06e5c",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure before experimentation provides no observable evidence-use process.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice is observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration is observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility details are supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection is observable.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "ae8e9ff96ba7e3d77c1206ddb68898630963c3d1bda5fbd65144de4fd85689d1",
        "trajectory_sha256": "bb14e619692a9a333761e37e3cb5cfd8b0d83ffc53eed435a6c366a4c03a08a5",
        "report_sha256": "7fd5d95badb5cbaba4bae46adff86a4dfee8678c674e6839de4985ff4100c09f"
      }
    },
    {
      "id": "deepseek--deepseek-v4-flash-high-load-seed-1",
      "model": "DeepSeek V4 Flash 0423",
      "effort": "high",
      "task": "load",
      "seed": 1,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "fd6ff876262a2c86914567dde5f0a8b3c11b6745829edc78fb5ba496f00318c9"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "99d2e007d3638d7aa1274a6f84bbe51c3961c2b76245e75e162edd54c50948f8",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure before experimentation; no evidence use observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice observable before failure.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility information observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection observable.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "72232a0ce7dff5432276369151a9be616df91e97f0d2010ca2c514644e3db7d0",
        "trajectory_sha256": "fd6ff876262a2c86914567dde5f0a8b3c11b6745829edc78fb5ba496f00318c9",
        "report_sha256": "dc0cbe24a032c7d5fdea9ef7691580318cf24d3579092352aebe28e600675d6a"
      }
    },
    {
      "id": "deepseek--deepseek-v4-flash-high-load-seed-2",
      "model": "DeepSeek V4 Flash 0423",
      "effort": "high",
      "task": "load",
      "seed": 2,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "e015bae65c27c7bd3f3377cbb7fef47efc3ec7874ab20af22bf9c9670d638d67"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "5da72f19eac66cdbcf7de10bb9658e0d786395c6e0314c789cff79f4e83fa0d2",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure before experimentation provides no observable evidence use.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice is observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration is observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility information is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection is observable.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "6d7c0591c17519790f3de70a519a2329b664bdebc8470e430bd5115f04036ac9",
        "trajectory_sha256": "e015bae65c27c7bd3f3377cbb7fef47efc3ec7874ab20af22bf9c9670d638d67",
        "report_sha256": "b082a9ecfff7da6adc4071a0652e0cba425f9da57f139d294813b08ac0ccc7ef"
      }
    },
    {
      "id": "deepseek--deepseek-v4-flash-high-pulse-seed-0",
      "model": "DeepSeek V4 Flash 0423",
      "effort": "high",
      "task": "pulse",
      "seed": 0,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "20981c22372f66904a3654f76e68ccd117bdb35ce5e8501113518d3ba4c0ab25"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "6799d2cd9dc0b4bf9216e86cecba53241aa94a0dd98674dc4afa310c382d9baf",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure before experimentation; no evidence use observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility information observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection observable.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "4b7b2896d0cc25b67feb623db4486f6de745e7b50dd1e943dd8315ad4f1e51e7",
        "trajectory_sha256": "20981c22372f66904a3654f76e68ccd117bdb35ce5e8501113518d3ba4c0ab25",
        "report_sha256": "58e7f2a24dc0df716674c9f2229c1d0a84a3fce122f0309331a4e5fcfdcf0c99"
      }
    },
    {
      "id": "deepseek--deepseek-v4-flash-high-pulse-seed-1",
      "model": "DeepSeek V4 Flash 0423",
      "effort": "high",
      "task": "pulse",
      "seed": 1,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "f31a45809f5c332e856a5ca76e4d15dc07b13f5e0f86283b028489c3da6f9191"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "fb425889bc119f13a5feb90aa0e6b909a3b6929f0539ea5263a9d2d469ba7e0b",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure before experimentation leaves evidence use unobservable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice is shown.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback integration is shown.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility evidence is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection is shown.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "095b8e372b948d9b787794d72fbfbe4b2cee869562e691f17f2b4c3105d72032",
        "trajectory_sha256": "f31a45809f5c332e856a5ca76e4d15dc07b13f5e0f86283b028489c3da6f9191",
        "report_sha256": "f61aab8c9620c54704c8b8587fe00bf5c30a668805d03eb39effa9e689bdf859"
      }
    },
    {
      "id": "deepseek--deepseek-v4-flash-high-pulse-seed-2",
      "model": "DeepSeek V4 Flash 0423",
      "effort": "high",
      "task": "pulse",
      "seed": 2,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "cb3a28f2eb7e4f9581c5d6705268b884e8b10a99eae56256eb73acd2bef5714d"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "436a862c7e64c8ca0a3e7575c5888749acb32eec547da737a6c09e74e59cabe1",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure before experimentation supplies no observable evidence-use process.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice is observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration is observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility details are supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection is observable.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "faa2f5c93974db2fd57aafe276d288bd40cc926c0c4d0d8270481402db49e492",
        "trajectory_sha256": "cb3a28f2eb7e4f9581c5d6705268b884e8b10a99eae56256eb73acd2bef5714d",
        "report_sha256": "e9d2f38568d8c79052a23a1c6070a445c03a4ff2625e90dee8bb7e86d679c1d2"
      }
    },
    {
      "id": "google--gemini-3-8-flash-medium-heat-seed-0",
      "model": "Gemini 3.8 Flash",
      "effort": "medium",
      "task": "heat",
      "seed": 0,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Baseline ridge regression model with alpha=10.0 on manifest data."
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Inspect baselines support for non-linear models (GBR/RF) or tune Ridge regulariz"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 0.49471412145615795
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Candidate 0 achieved the lowest person MAE (0.4899 vs 0.4947 for candidate 1) us"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "9499c6ea43858de5462b35e4aa395ad6e2a3f100e0fb11a5f0080e93e8f64618"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "c96d08a83cb7564988e17bb8e66b11b239ba7a769f9f5fc07da904837cb26021",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Uses both valid development losses to support selection; evidence is limited to two aggregate results.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Establishes a specified Ridge baseline, but the follow-up mixes model inspection and tuning without a precise change or hypothesis.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "feedback",
              "reason": "Final selection incorporates measured feedback, but the follow-up does not explain how the initial result informed its design.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00010"
              ],
              "id": "repro",
              "reason": "Script filenames, one hyperparameter, and valid runs are recorded; implementation, data configuration, and execution instructions are not supplied.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Selects the lower-loss valid candidate and accurately cites both observed losses.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "38bfe4c0dbe89d2bacac23a5f439af48a1f414f0d9ec48561fadeb9339b93e92",
        "trajectory_sha256": "9499c6ea43858de5462b35e4aa395ad6e2a3f100e0fb11a5f0080e93e8f64618",
        "report_sha256": "7c6ce9d163b895773e4db10bb11c520424162597a2ed6f343abbc468428c8e53"
      }
    },
    {
      "id": "google--gemini-3-8-flash-medium-heat-seed-1",
      "model": "Gemini 3.8 Flash",
      "effort": "medium",
      "task": "heat",
      "seed": 1,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Baseline Ridge regression with alpha=10 to establish benchmark rectal temperatur"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "746a621d834192ce515258541ce633b5065f302ecd695d7ee45ddc72b90462e5"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "f32bf24ac775b74cf648fe5777604f553a0556e4a706e1ddd0596d42bdd5b0d1",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00001"
              ],
              "id": "evidence",
              "reason": "Baseline hypothesis is stated, but no supporting data inspection or evidence-based rationale for Ridge or alpha=10 is supplied.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "experiment",
              "reason": "A concrete baseline experiment executes successfully and returns a loss; no comparison or targeted follow-up is shown.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005"
              ],
              "id": "feedback",
              "reason": "A development result is supplied, but no subsequent decision shows how feedback was integrated.",
              "score": null
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "repro",
              "reason": "Script reference, estimator, alpha, and loss are recorded, but code contents, data split, and execution details are absent.",
              "score": 1
            },
            {
              "evidence_ids": [],
              "id": "selection",
              "reason": "No final selection decision is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "706e759661d0f840ddc55d4d20564fd66934896de5fb4fd21b0c9e96a77e3bdb",
        "trajectory_sha256": "746a621d834192ce515258541ce633b5065f302ecd695d7ee45ddc72b90462e5",
        "report_sha256": "d62f1f07046a175e03f912e4d0e0fdec13c642071574d2aeb65d796f9317cfcb"
      }
    },
    {
      "id": "google--gemini-3-8-flash-medium-heat-seed-2",
      "model": "Gemini 3.8 Flash",
      "effort": "medium",
      "task": "heat",
      "seed": 2,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Train baseline ridge regression model with alpha=10 on manifest data."
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "89769e3cca02641143b875e79e9c45678c0b4f64def0d74d7f0428d2657a4b57"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "d2bb71037c4a134122d5f86af96ac12d778f8c70a7b8e3c81a232e36914b15a8",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "evidence",
              "reason": "A baseline hypothesis and valid measured loss are supplied, but no evidence-based interpretation is shown.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00001"
              ],
              "id": "experiment",
              "reason": "Ridge with alpha=10 is a concrete baseline experiment, but no rationale for the setting or comparison is supplied.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005"
              ],
              "id": "feedback",
              "reason": "A development result is available, but no subsequent decision shows whether it was integrated.",
              "score": null
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "repro",
              "reason": "Algorithm, alpha, script reference, and successful execution are recorded; script contents and data or evaluation details are absent.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "selection",
              "reason": "No final selection or selection rationale is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "3438d2ba0b104756334e92d56f2056ae84bb7645188db2ecb03db4fe2b08ce7b",
        "trajectory_sha256": "89769e3cca02641143b875e79e9c45678c0b4f64def0d74d7f0428d2657a4b57",
        "report_sha256": "e1c3845f8e38dbb37e74848817f663dc21ad7821217312d03ca80faf8e135633"
      }
    },
    {
      "id": "google--gemini-3-8-flash-medium-load-seed-0",
      "model": "Gemini 3.8 Flash",
      "effort": "medium",
      "task": "load",
      "seed": 0,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Train baseline ridge regression model with alpha=10 using task baseline helper."
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 32.159375997346515
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Train gradient boosting regressor baseline using task helper to capture nonlinea"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Missing artifact",
            "id": "e00009",
            "kind": "development_result",
            "primary_loss": null
          },
          {
            "evidence_ids": [
              "e00005",
              "e00009"
            ],
            "id": "e00010",
            "kind": "final_selection",
            "reason": "Select candidate 0 (ridge alpha=10) with person MAE of 32.16 W as the only valid"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "4aef60b773e7a1763deaa513ad5fb104e10bd23eb744b445f07c63f4373eec4c"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "00b875a64882332ec89a03d33a54c02d893797f533a4062902eb31f8345f49b4",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00009",
                "e00010"
              ],
              "id": "evidence",
              "reason": "Selection correctly uses the observed loss and distinguishes valid from failed execution; evidence is limited to two trials.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Ridge and gradient boosting provide a reasonable linear/nonlinear comparison, but no systematic tuning or detailed experimental rationale is shown.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00009",
                "e00010"
              ],
              "id": "feedback",
              "reason": "Validity feedback informs selection, but no repair or follow-up investigation of the missing artifact is shown.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00009"
              ],
              "id": "repro",
              "reason": "Script references and ridge alpha are supplied, but script contents, data splits, environment, and other settings are absent; the second trial lacks an artifact.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00009",
                "e00010"
              ],
              "id": "selection",
              "reason": "Chooses the only valid candidate, accurately reports its observed loss, and explicitly cites both trial outcomes.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "1e0a601c885c160e2e93f0519383abf23e6cfdf2f94e1206f6a621e77d9037b7",
        "trajectory_sha256": "4aef60b773e7a1763deaa513ad5fb104e10bd23eb744b445f07c63f4373eec4c",
        "report_sha256": "1edd0071d9e763c5babb5a18f1a1398f9dcf94a86e1332ad1e32a3d94888a8f7"
      }
    },
    {
      "id": "google--gemini-3-8-flash-medium-load-seed-1",
      "model": "Gemini 3.8 Flash",
      "effort": "medium",
      "task": "load",
      "seed": 1,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Establish baseline Ridge model with alpha=10 using baseline helper."
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 32.159375997346515
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Inspect baseline implementation and manifest structure to design an improved mod"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Missing artifact",
            "id": "e00009",
            "kind": "development_result",
            "primary_loss": null
          },
          {
            "evidence_ids": [
              "e00005",
              "e00009"
            ],
            "id": "e00010",
            "kind": "final_selection",
            "reason": "Select experiment 0 baseline Ridge model achieving person MAE of 32.16 W on trai"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "dde731b69bf96428dfb3e9528e65a0046f13e6ff10ce285a75a05351068856fb"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "4dc055e90246356df21229808942c8e551114330418346c6eb77e1a608bdb92e",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00009",
                "e00010"
              ],
              "id": "evidence",
              "reason": "Final choice cites the valid baseline loss and failed alternative, but no deeper evidence analysis is shown.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00009"
              ],
              "id": "experiment",
              "reason": "Establishes a concrete Ridge baseline; the second experiment proposes inspection rather than a specified model change and fails for a missing artifact.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00009",
                "e00010"
              ],
              "id": "feedback",
              "reason": "Retains the successful baseline after the alternative fails, but shows no targeted response to baseline performance or repair of the artifact failure.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00006",
                "e00009"
              ],
              "id": "repro",
              "reason": "Script references, Ridge alpha, and execution outcomes provide partial traceability; code contents, data setup, and evaluation procedure are absent.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00009",
                "e00010"
              ],
              "id": "selection",
              "reason": "Selects the only execution-valid candidate and accurately reports its observed loss; the comparison is limited to one successful run.",
              "score": 3
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "bdd2782c69e007a6ec6c399e7424da8e808cd656f9d0b080726c783730cfd5b5",
        "trajectory_sha256": "dde731b69bf96428dfb3e9528e65a0046f13e6ff10ce285a75a05351068856fb",
        "report_sha256": "5b2c3084e9c10e07f61166a613c143a845c89ca4566e7c5d019008ffe3936124"
      }
    },
    {
      "id": "google--gemini-3-8-flash-medium-load-seed-2",
      "model": "Gemini 3.8 Flash",
      "effort": "medium",
      "task": "load",
      "seed": 2,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Train baseline Ridge regression (alpha=10.0) on manifest data."
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 32.159375997346515
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "fec8e53786305ed3280b5f46fe1250ab371dd0d37ee6a0a86d0a7acec4bdb8fb"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "6fd933d3b32227386fb600f2314f9b4e83f7f0d6bf21b3e5786b51255adad32b",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "evidence",
              "reason": "Records a baseline loss, but no data analysis or evidence-based justification for the configuration is shown.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "experiment",
              "reason": "A valid Ridge baseline with explicit alpha is a reasonable initial experiment; no comparisons or targeted follow-up are supplied.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005"
              ],
              "id": "feedback",
              "reason": "A result is supplied, but no subsequent decision shows whether feedback was incorporated.",
              "score": null
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "repro",
              "reason": "Names a script and alpha and reports successful execution, but omits script contents, data preparation, and evaluation split details.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "selection",
              "reason": "No explicit final selection or selection rationale is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "8b9a935c185ef0637a348615ee5bf63bdf46a0b7bf3bbd143f87d17397c7c27b",
        "trajectory_sha256": "fec8e53786305ed3280b5f46fe1250ab371dd0d37ee6a0a86d0a7acec4bdb8fb",
        "report_sha256": "1d46b27792a299abafa2b46ea66e0001b544eb0c313536633707861a1041c5ee"
      }
    },
    {
      "id": "google--gemini-3-8-flash-medium-pulse-seed-0",
      "model": "Gemini 3.8 Flash",
      "effort": "medium",
      "task": "pulse",
      "seed": 0,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Fit baseline Ridge regression (alpha=10) on trailing PPG and accelerometer featu"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "c0b6f82d3a4ddf2b253fb18867edc586c9b0d05ce9973ee69c6d1db70605c35d"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "f60801356c084220f735ffdf9e9d072356970bc73071860e16708f2d48b177ab",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "evidence",
              "reason": "A baseline and its development loss are recorded, but no evidence-based interpretation or comparison is shown.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00001"
              ],
              "id": "experiment",
              "reason": "Ridge with alpha=10 and trailing PPG/accelerometer features is a concrete baseline, but the hypothesis is truncated and no rationale or comparison is supplied.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005"
              ],
              "id": "feedback",
              "reason": "A valid development result is visible, but no subsequent decision shows how feedback was integrated.",
              "score": null
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "repro",
              "reason": "The trial filename, estimator, alpha, feature outline, and loss are recorded; code contents, data split, and execution details are absent.",
              "score": 1
            },
            {
              "evidence_ids": [],
              "id": "selection",
              "reason": "No final selection decision is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "5903f468b0fb6329edbba41130efec0d3a7d4d9aa92ebeb4af80858e457e3b78",
        "trajectory_sha256": "c0b6f82d3a4ddf2b253fb18867edc586c9b0d05ce9973ee69c6d1db70605c35d",
        "report_sha256": "cb1380a077a48e453fe7bfa4e17efbd3addf4c37fe77e0851b0f1300c3d5c2b1"
      }
    },
    {
      "id": "google--gemini-3-8-flash-medium-pulse-seed-1",
      "model": "Gemini 3.8 Flash",
      "effort": "medium",
      "task": "pulse",
      "seed": 1,
      "execution_valid": false,
      "status": "missing",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "dac507cbf6a98778e2b3ace75d785062d017615463b6e6f08c16ca44f79b5025"
      },
      "report": null,
      "provenance": {
        "receipt_sha256": "073fee25ec30c6e4e2059bf2970e7ebd9b1013cc6bb01884087beefa44fb4d1b",
        "trajectory_sha256": "dac507cbf6a98778e2b3ace75d785062d017615463b6e6f08c16ca44f79b5025",
        "report_sha256": null
      }
    },
    {
      "id": "google--gemini-3-8-flash-medium-pulse-seed-2",
      "model": "Gemini 3.8 Flash",
      "effort": "medium",
      "task": "pulse",
      "seed": 2,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Run baseline ridge training to produce candidate 1 and inspect baselines impleme"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Try random forest baseline or tuned ridge on manifest to improve person MAE."
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 12.932933545827353
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Candidate 1 achieved lower person MAE (12.9329 vs 12.9338 for candidate 0)."
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "8297b29551a87c7b239f0f534785087c4697c3cf3b47c0051fd7e2eb9b5b805e"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "9e0718d1a270108f305f3a02d8ec10941c33dab3951c4839d82ab42649d99f68",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Uses both reported development losses for comparison, but supplies no diagnostic or uncertainty analysis.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Baseline followed by a plausible improvement trial; the second hypothesis is ambiguous between random forest and tuned ridge and lacks specific settings.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006"
              ],
              "id": "feedback",
              "reason": "A follow-up improvement attempt is visible, but no explicit interpretation of baseline feedback or result-driven change is documented.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00006",
                "e00010"
              ],
              "id": "repro",
              "reason": "Script filenames and successful execution are recorded, but code contents, configurations, seeds, and execution instructions are absent.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Correctly selects the lower observed development loss and cites both results; the very small improvement is not checked for stability.",
              "score": 3
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "84cf627878e8b2316c2f652a51e5d99331a0cec4f8fb04d0afbbd17556a2f1e3",
        "trajectory_sha256": "8297b29551a87c7b239f0f534785087c4697c3cf3b47c0051fd7e2eb9b5b805e",
        "report_sha256": "bee62e832f8ce6f4044e3d3847217766b8b6e483679b85e0c8da19c1f1e7428d"
      }
    },
    {
      "id": "google--gemini-4-argon-medium-heat-seed-0",
      "model": "Gemini 4 Argon",
      "effort": "medium",
      "task": "heat",
      "seed": 0,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Inspect baseline source code, data dictionary, and run default ridge baseline to"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Inspect baseline inference structure and evaluate tuned regularization and ensem"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Both valid candidates achieved identical primary loss (0.489896 MAE); selecting "
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "a08de968c3f1408ae037680232ddfb8caec22b5559012ea1097cb1038f5dc9b8"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "0e5bd6be3673b467b91050dc4c373d0ef50eb06ba0484c7306bcaf72dfaae3e7",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Final reasoning cites both observed valid losses and correctly recognizes their equality; no richer analysis is supplied.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Baseline followed by regularization and ensemble exploration is reasonable, but truncated hypotheses and absent implementation details limit assessment of experimental control.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "feedback",
              "reason": "A follow-up experiment occurs after the baseline result and the final reasoning acknowledges the tie, but no explicit result-driven adjustment is documented.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00010"
              ],
              "id": "repro",
              "reason": "Trial filenames and valid reported losses provide minimal traceability, but code contents, configurations, seeds, and execution instructions are absent.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Selection reasoning correctly compares the two valid candidates using primary loss, but the truncated record does not identify the chosen candidate or tie-break rule.",
              "score": 2
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "a3583b85960b5d24138e011ca4a6ff448e1169ca888980213ac1af1d1b0a66ef",
        "trajectory_sha256": "a08de968c3f1408ae037680232ddfb8caec22b5559012ea1097cb1038f5dc9b8",
        "report_sha256": "ec99e84b33f91c83f288cba12c564e7159f9c0112a98c2f5f5a6975f67995890"
      }
    },
    {
      "id": "google--gemini-4-argon-medium-heat-seed-1",
      "model": "Gemini 4 Argon",
      "effort": "medium",
      "task": "heat",
      "seed": 1,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Inspect task data dictionary, baseline implementation, and trial0 while running "
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Run ridge baseline and inspect heat baseline internals and manifest structure to"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Artifact must include inference.py with predict(artifact_dir, reques",
            "id": "e00009",
            "kind": "development_result",
            "primary_loss": null
          },
          {
            "evidence_ids": [
              "e00005",
              "e00009"
            ],
            "id": "e00010",
            "kind": "final_selection",
            "reason": "Candidate 0 (evidence e00005) is the only valid evaluated artifact, achieving a "
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "76cc99a0b6bfc299038fc9c9b1806edc3f87b6731f0197c74e77439effedab5e"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "7cbffa15c5fc8993c2b52071032da1baeae70bcb7af7efc23e4c5b7a5eb68a11",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00010"
              ],
              "id": "evidence",
              "reason": "Plans mention inspecting task data and baseline internals; final choice cites observed results, but no substantive inspection findings are supplied.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00009"
              ],
              "id": "experiment",
              "reason": "Two baseline trials provide a limited comparison; hypotheses are truncated and one trial fails artifact validation.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00009",
                "e00010"
              ],
              "id": "feedback",
              "reason": "Selection incorporates validity feedback by choosing the sole valid artifact, but no repair or iterative response to the failure is shown.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00009"
              ],
              "id": "repro",
              "reason": "Trial filenames and evaluation outcomes are recorded, but code contents, settings, and reproduction commands are absent.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00009",
                "e00010"
              ],
              "id": "selection",
              "reason": "Selects the only valid evaluated candidate and explicitly cites both results; supported by observed validity and loss, though comparison is limited.",
              "score": 3
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "81f8eb729ee37b2c5ebc2c7dc6bf83f9639b85c6c187002ab2592c817b521feb",
        "trajectory_sha256": "76cc99a0b6bfc299038fc9c9b1806edc3f87b6731f0197c74e77439effedab5e",
        "report_sha256": "6f70f6286dc7f10851874bbf25a540c6c183e3f533971eff2d489830547ad2be"
      }
    },
    {
      "id": "google--gemini-4-argon-medium-heat-seed-2",
      "model": "Gemini 4 Argon",
      "effort": "medium",
      "task": "heat",
      "seed": 2,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Run baseline ridge model and inspect baseline implementation and trial0.py to pr"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "00485675b2a49dc963a3c43f666fefb39c7e0b13dd1025b5b83d790836ec64be"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "620fd836b74aaff33669b29ed4b4a8f96919c5a6b31a30d96e2dc769222fde6d",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "evidence",
              "reason": "A baseline run produced a valid loss, but no interpretation or evidence-based comparison is shown.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "experiment",
              "reason": "Running a ridge baseline is a reasonable initial experiment and executed successfully; no controlled comparison is supplied.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005"
              ],
              "id": "feedback",
              "reason": "A result is supplied, but no subsequent decision shows whether feedback was integrated.",
              "score": null
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "repro",
              "reason": "The trial filename, execution status, and loss are recorded, but code contents, configuration, and evaluation procedure are absent.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "selection",
              "reason": "No final selection or selection rationale is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "1b5f110a99161c95474fd56f514c604ae3f1176e815389dfba1f095caff8e4aa",
        "trajectory_sha256": "00485675b2a49dc963a3c43f666fefb39c7e0b13dd1025b5b83d790836ec64be",
        "report_sha256": "52dedaa89b85cb6d6848e6a82d46c540991cb8e37a7f3806af78da857428ff63"
      }
    },
    {
      "id": "google--gemini-4-argon-medium-load-seed-0",
      "model": "Gemini 4 Argon",
      "effort": "medium",
      "task": "load",
      "seed": 0,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Inspect data dictionary, baseline implementation, and run baseline ridge model f"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 32.159375997346515
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Wait - let me finish writing the full CV + physics feature engineering + model s"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 32.159375997346515
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Select candidate 0 (e00005), which executed cleanly and achieved a validated per"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "67405bc63aeecf04119b5044dd61379ddc763c440d1c5280a3edf115a8b028c5"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "88dca88c55905c278a17362476558d2c9c876b87cfb5d92dc5de62d46d06415e",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Records baseline intent and two valid losses; final choice cites both results, but no substantive data inspection or comparative analysis is visible.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Baseline ridge and proposed CV/physics features provide a plausible direction, but hypotheses are truncated and no controlled experimental distinction is shown.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010"
              ],
              "id": "feedback",
              "reason": "A follow-up experiment follows the baseline result, but does not explicitly interpret it; identical reported losses receive no visible diagnosis.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00010"
              ],
              "id": "repro",
              "reason": "Script filenames and successful execution results are recorded, but code contents, settings, data splits, and execution instructions are absent.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Explicitly selects a successfully executed candidate and cites both observed results; selecting candidate 0 is consistent with their tied losses, though the rationale is truncated.",
              "score": 3
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "0ed82084675d101646d72f4a8a412f3d7a1361752016809e6ac258edbc305ddc",
        "trajectory_sha256": "67405bc63aeecf04119b5044dd61379ddc763c440d1c5280a3edf115a8b028c5",
        "report_sha256": "e03e12e624258a8c4b5a5c1662b8bf5eae233eeaa745f5777412d800371daab5"
      }
    },
    {
      "id": "google--gemini-4-argon-medium-load-seed-1",
      "model": "Gemini 4 Argon",
      "effort": "medium",
      "task": "load",
      "seed": 1,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Inspect baseline implementation, data dictionary, manifest, and trial0.py while "
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 33.749958301747775
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "97a3cd398b6170d334093a5d71bb32df06adba871515a09954a2bf82523b197c"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "2618693cdf18732ae47a5a1a2aab53833320017dc75dd0d9b84713522150eb58",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00001"
              ],
              "id": "evidence",
              "reason": "Names baseline and data artifacts for inspection but supplies no findings or evidence-linked rationale.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "experiment",
              "reason": "One valid trial is reported, but the hypothesis is incomplete and no specific change or comparison is described.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005"
              ],
              "id": "feedback",
              "reason": "A loss is reported, but no subsequent interpretation or response is observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "repro",
              "reason": "Trial filename, execution validity, and loss are supplied; code contents, configuration, and execution procedure are absent.",
              "score": 1
            },
            {
              "evidence_ids": [],
              "id": "selection",
              "reason": "No final selection or selection rationale is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "8a2648589cc58dc19f7a6c84e3926e00eeba9793a219d9a4b57d98f325b3408e",
        "trajectory_sha256": "97a3cd398b6170d334093a5d71bb32df06adba871515a09954a2bf82523b197c",
        "report_sha256": "1ecf0f850dc40cbb85b2432570765ce4aa97b9562d5d5499b7c7ae18e2b28b02"
      }
    },
    {
      "id": "google--gemini-4-argon-medium-load-seed-2",
      "model": "Gemini 4 Argon",
      "effort": "medium",
      "task": "load",
      "seed": 2,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Inspect baselines.py and trial0.py while running the baseline ridge model with s"
            },
            "id": "e00002",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00006",
            "kind": "development_result",
            "primary_loss": 32.159375997346515
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Evaluate gradient boosting baseline with seed=2 and inspect baselines.py impleme"
            },
            "id": "e00007",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Missing artifact",
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": null
          },
          {
            "evidence_ids": [
              "e00006",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Candidate 0 (ridge baseline) is the only valid evaluated artifact, achieving a p"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "ac494ee56ca791bc62056492df8fdc6a02b40446fe1bbf11ecb673820b048d8b"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "5d792697a33cae0e70888fe0c6dfbd4d1af822310cffbcc41282d3f2db612a7e",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Selection uses observed validity and loss, but evidence is limited to one successful evaluation and one artifact failure.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00002",
                "e00007"
              ],
              "id": "experiment",
              "reason": "Tests two plausible baselines, ridge and gradient boosting; hypotheses provide little detail on expected improvements or controlled comparisons.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00010",
                "e00011"
              ],
              "id": "feedback",
              "reason": "Accounts for the missing-artifact failure in selection, but no repair or follow-up evaluation is shown.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00002",
                "e00007",
                "e00006",
                "e00010"
              ],
              "id": "repro",
              "reason": "Trial filenames, one seed, and outcomes are recorded, but executable code, full configurations, and evaluation setup are not supplied.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Selects the only valid evaluated artifact, consistent with the supplied results rather than the failed alternative.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "3971adb7a938adbfc9f0cd349b80aeeb32692b5f9ea64a5fcc05d62311b34e7a",
        "trajectory_sha256": "ac494ee56ca791bc62056492df8fdc6a02b40446fe1bbf11ecb673820b048d8b",
        "report_sha256": "aef0b85cef4698c0519431aa5da3300b3426585ccba043e42170cd737493c7d6"
      }
    },
    {
      "id": "google--gemini-4-argon-medium-pulse-seed-0",
      "model": "Gemini 4 Argon",
      "effort": "medium",
      "task": "pulse",
      "seed": 0,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Inspect baselines source and data dictionary while running baseline ridge model "
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "42ce9262bd88e7ee155599d426f20be1ec8611688d9eca12b876647a6dd0dee7"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "bdbc322fc869a67c7d4c2eee37bfbf6e72f1aa951128a7ae3ee01aff282c48ba",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "evidence",
              "reason": "Inspection is proposed and a baseline loss is reported, but no inspection findings or use of evidence in a decision are shown.",
              "score": null
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "experiment",
              "reason": "A ridge baseline is a reasonable initial experiment and executes successfully; no specific hypothesis, comparison, or design rationale is supplied.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005"
              ],
              "id": "feedback",
              "reason": "A loss is available, but no subsequent response to that feedback is shown.",
              "score": null
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "repro",
              "reason": "A script filename and successful execution with a numeric loss are recorded, but code, data setup, configuration, and evaluation procedure are absent.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "selection",
              "reason": "No final selection or selection rationale is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "c505fc5e22ea6307d0a907ba015e1604e8957d14c3e5c4368d24e7f71aa08dbc",
        "trajectory_sha256": "42ce9262bd88e7ee155599d426f20be1ec8611688d9eca12b876647a6dd0dee7",
        "report_sha256": "cf1ffa43441d46e2bbc86a28936222c118df792304773fa617789ccd3391d80d"
      }
    },
    {
      "id": "google--gemini-4-argon-medium-pulse-seed-1",
      "model": "Gemini 4 Argon",
      "effort": "medium",
      "task": "pulse",
      "seed": 1,
      "execution_valid": false,
      "status": "missing",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Inspect data dictionary, baseline implementation, and run ridge baseline with se"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Inspect baseline source and manifest while producing a valid artifact."
            },
            "id": "e00007",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00012",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "5fa976f3ca4517cfeb6b7562375f51190d20bf1cfe01b82908f572a0529084dd"
      },
      "report": null,
      "provenance": {
        "receipt_sha256": "d6ac781e6726af3827fae13a81346772dad0d95dd2df994ceba7af710752ada0",
        "trajectory_sha256": "5fa976f3ca4517cfeb6b7562375f51190d20bf1cfe01b82908f572a0529084dd",
        "report_sha256": null
      }
    },
    {
      "id": "google--gemini-4-argon-medium-pulse-seed-2",
      "model": "Gemini 4 Argon",
      "effort": "medium",
      "task": "pulse",
      "seed": 2,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Inspect baseline implementation, data dictionary, and run default ridge baseline"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Inspect baseline feature extraction and train higher-regularization ridge model "
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00011",
            "kind": "development_result",
            "primary_loss": 12.944129682708398
          },
          {
            "evidence_ids": [
              "e00005",
              "e00011"
            ],
            "id": "e00012",
            "kind": "final_selection",
            "reason": "Candidate 0 achieved a lower primary loss (12.9338 vs 12.9441 in e00011) as evid"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "0cd3d0b7371c7977414ca0d90849524f880a2984ca718740959eeb0f3450228d"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "cd34d4a76786596f885d2fced9a2188c00e8a55f61d2e8e976881659be61ce15",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00011",
                "e00012"
              ],
              "id": "evidence",
              "reason": "Selection explicitly compares both observed development losses; no broader diagnostic evidence is supplied.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Baseline followed by a higher-regularization ridge trial is a coherent narrow comparison, but the regularization change lacks a specific diagnostic justification.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00011",
                "e00012"
              ],
              "id": "feedback",
              "reason": "Development results inform final selection, but no explicit interpretation of baseline feedback motivates the subsequent trial.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00011"
              ],
              "id": "repro",
              "reason": "Trial filenames and valid execution outcomes are recorded, but supplied evidence lacks code contents, parameter values, and evaluation setup needed to reproduce results.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00011",
                "e00012"
              ],
              "id": "selection",
              "reason": "Correctly selects the lower-loss candidate and cites both comparison results.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "53cc8c20e1592e9bc1ea924d1de433b38c08653d1c1b38c0426063e6fe1191ae",
        "trajectory_sha256": "0cd3d0b7371c7977414ca0d90849524f880a2984ca718740959eeb0f3450228d",
        "report_sha256": "0c0407d2785a3bf8a8ccac3dbac28fef8af6d267f3e922e37a67709194f2bbf2"
      }
    },
    {
      "id": "moonshotai--kimi-k3-high-heat-seed-0",
      "model": "Kimi K3",
      "effort": "high",
      "task": "heat",
      "seed": 0,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Experiment 1: inspect data dictionary, manifest, and prior trial before writing "
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Missing artifact",
            "id": "e00004",
            "kind": "development_result",
            "primary_loss": null
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Use the supplied ridge baseline with trial seed 0; it trains from the staged man"
            },
            "id": "e00005",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00009",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          },
          {
            "evidence_ids": [
              "e00004",
              "e00009"
            ],
            "id": "e00010",
            "kind": "final_selection",
            "reason": "Candidate 1 is the only execution-valid artifact; ridge seed 0 completed with pe"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "369052cbd13359c3491095447138e2bbc6638ec6dd5f02ea5dd5d7c739a057d2"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "346819c25210e6ff66f5f7dcd05c4f7cf1345f1de7d98c80c254270b03af766a",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00001",
                "e00004",
                "e00005",
                "e00009",
                "e00010"
              ],
              "id": "evidence",
              "reason": "Uses observed execution validity to select the baseline, but no actual dictionary, manifest, or prior-trial findings are supplied.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00004",
                "e00005",
                "e00009"
              ],
              "id": "experiment",
              "reason": "Falls back to a supplied ridge baseline after a missing-artifact failure; sensible recovery, but limited comparative experimentation or hypothesis testing.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00004",
                "e00005",
                "e00009"
              ],
              "id": "feedback",
              "reason": "The next attempt succeeds after the missing-artifact failure, though the supplied record does not explain the specific corrective change.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00009"
              ],
              "id": "repro",
              "reason": "Trial filenames, baseline type, seed 0, and a numeric result are recorded; code contents, full configuration, and data details are absent.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00004",
                "e00009",
                "e00010"
              ],
              "id": "selection",
              "reason": "Explicitly selects the only execution-valid candidate and cites both results; the observed evidence supports that choice without implying broader superiority.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "fe92edf713e4129bd7b6b79c4f631bc06b3020c4f6808e5a1cd9f1082b381c9c",
        "trajectory_sha256": "369052cbd13359c3491095447138e2bbc6638ec6dd5f02ea5dd5d7c739a057d2",
        "report_sha256": "bed67e71c5b29e9b4d98a37b27639dcb44677e0f8d525bb636205c33928f9f9d"
      }
    },
    {
      "id": "moonshotai--kimi-k3-high-heat-seed-1",
      "model": "Kimi K3",
      "effort": "high",
      "task": "heat",
      "seed": 1,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "b6075f2d6f4918cb14049f693020d6e1fcc42c2db9abcbb96e3794cf0b244bc0"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "d0a43ca12d9adaf539e9e559ba9384e574a8a89d4d6b0a9b0fee999d20d35e7d",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure before experimentation; evidence use is unobservable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice is shown.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration is shown.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility details are shown.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection is shown.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "f96bb19c54954b749605f3e52f7a411f3fafd545b1bbfd459f624b281d72e5bc",
        "trajectory_sha256": "b6075f2d6f4918cb14049f693020d6e1fcc42c2db9abcbb96e3794cf0b244bc0",
        "report_sha256": "2822cda77a6a7bb4ee0d2fed795b62085bb2036ef4f31e67081f8c74d1b5e635"
      }
    },
    {
      "id": "moonshotai--kimi-k3-high-heat-seed-2",
      "model": "Kimi K3",
      "effort": "high",
      "task": "heat",
      "seed": 2,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "bbfd0bbc44bdc650c719016584db48969fa122dd372219c8edfc6ecd6bbeddc0"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "709f199e35e913159418cc1e5b92ec5ba45c3cfdab21eec41a96a30d87095d33",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failed before experimentation; evidence use is unobservable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility details are supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "e62752b89ad43303a06215aeba874d3d3ab9a5dec6708d008edec70a996cb374",
        "trajectory_sha256": "bbfd0bbc44bdc650c719016584db48969fa122dd372219c8edfc6ecd6bbeddc0",
        "report_sha256": "ecf2fa79edc477a105ef7c7e529708c62a357bbba1a357854c2e2d2e6acc0ee1"
      }
    },
    {
      "id": "moonshotai--kimi-k3-high-load-seed-0",
      "model": "Kimi K3",
      "effort": "high",
      "task": "load",
      "seed": 0,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "46ba8de62b05f90089f1de5919a4a1ac0d77e628def7c089a068ab6aca6f1193"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "782e4b3836c507cb3c4d4c0ed5bbacafc914be178020e086500fb65c3e44c31b",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure before experimentation; no evidence use observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice observable before failure.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility information observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection observable.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "af588a2db636ed960ad192a259ac8c86342144c902824d7005968764356b84d8",
        "trajectory_sha256": "46ba8de62b05f90089f1de5919a4a1ac0d77e628def7c089a068ab6aca6f1193",
        "report_sha256": "33a46823be725a7b3c06a101e93daeb5ec6b78618cdcd2d086cac47be1bd2509"
      }
    },
    {
      "id": "moonshotai--kimi-k3-high-load-seed-1",
      "model": "Kimi K3",
      "effort": "high",
      "task": "load",
      "seed": 1,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Exp1 uses the supplied ridge baseline with seed 1 and alpha 10, establishing a r"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 32.159375997346515
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "aa0f5087ed730268524d7a9051b2bd5e7a342700f3af46a2cbe75927649b9ba2"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "14074ff32d8c89333d5f81605a8560ddcb01a5f1f2c51cf8b955ecb0bc045119",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00001"
              ],
              "id": "evidence",
              "reason": "References a supplied baseline, but provides no supporting analysis or evidence-based rationale.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "experiment",
              "reason": "Runs a concrete ridge baseline with specified seed and alpha; execution succeeds, but no comparison is shown.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005"
              ],
              "id": "feedback",
              "reason": "A loss is reported, but no subsequent decision shows whether feedback was integrated.",
              "score": null
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "repro",
              "reason": "Records seed, alpha, script reference, and loss, but script contents and data/evaluation setup are absent.",
              "score": 2
            },
            {
              "evidence_ids": [],
              "id": "selection",
              "reason": "No final selection is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "8104ca8e9c29495a69bdd2d7fbf298ac5149f6e502b54374aa60db323249c3fb",
        "trajectory_sha256": "aa0f5087ed730268524d7a9051b2bd5e7a342700f3af46a2cbe75927649b9ba2",
        "report_sha256": "c8ee64431ac819cec626a9441f0c97b18a20c419f2ef9f422aa2a7a111490708"
      }
    },
    {
      "id": "moonshotai--kimi-k3-high-load-seed-2",
      "model": "Kimi K3",
      "effort": "high",
      "task": "load",
      "seed": 2,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "6ed35aff6bd87b0ba773563bbfa81a4c56a2691f759dbf46751cd405272c2844"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "eadb7eab13dcbeb3887e2df7af15c07fd55ee4b5a6f7fc34edc8f0178da9f7ff",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure before experimentation supplies no observable evidence use.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice is observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration is observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility information is observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection is observable.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "a3a4393f608202f402fb0d967c4070a3dd3510a0aa02c981d68e9202aed46017",
        "trajectory_sha256": "6ed35aff6bd87b0ba773563bbfa81a4c56a2691f759dbf46751cd405272c2844",
        "report_sha256": "a72d9e555352eb78b18256e9fa2a722cf3f34ac0bf293220ee4903c3553a1581"
      }
    },
    {
      "id": "moonshotai--kimi-k3-high-pulse-seed-0",
      "model": "Kimi K3",
      "effort": "high",
      "task": "pulse",
      "seed": 0,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Uses the supplied evaluated ridge baseline with trial seed 0 and only staged man"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Artifact must include inference.py with predict(artifact_dir, reques",
            "id": "e00004",
            "kind": "development_result",
            "primary_loss": null
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Rerun the evaluated ridge baseline with seed 0 after removing any stale artifact"
            },
            "id": "e00005",
            "kind": "experiment"
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Rerun the evaluated ridge baseline with seed 0 after removing any stale artifact"
            },
            "id": "e00008",
            "kind": "experiment"
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Rerun the evaluated ridge baseline with seed 0 after removing any stale artifact"
            },
            "id": "e00011",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00015",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          },
          {
            "evidence_ids": [
              "e00004",
              "e00015"
            ],
            "id": "e00016",
            "kind": "final_selection",
            "reason": "Candidate 1 is the only valid evaluated artifact; the seed-0 ridge rerun succeed"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "dc869c0cda073073d0d4e7ab89db262235be5b068f17c7b8971df30396381228"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "0a08e883bcde9411f3542d65132013a2606a10ee05d88ba59787083e390d9799",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00004",
                "e00015",
                "e00016"
              ],
              "id": "evidence",
              "reason": "Selection explicitly uses observed execution validity and the successful evaluation; little broader evidence analysis is visible.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00008",
                "e00011",
                "e00015"
              ],
              "id": "experiment",
              "reason": "Baseline reruns recover a valid evaluation, but repeated identical hypotheses offer limited comparative or diagnostic value.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00004",
                "e00005",
                "e00015"
              ],
              "id": "feedback",
              "reason": "A rerun follows the artifact-interface failure and eventually succeeds, but the stated stale-artifact remedy does not explicitly address the missing inference interface.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00015"
              ],
              "id": "repro",
              "reason": "Trial filenames, seed 0, and an evaluation loss are recorded, but code contents, execution commands, and complete artifact details are absent.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00004",
                "e00015",
                "e00016"
              ],
              "id": "selection",
              "reason": "Chooses the only valid evaluated artifact and explicitly cites both evaluation outcomes, without claiming unsupported comparative performance.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "40f84be3dc54e774f2cd384ae0189ad7f617680828f521ca9793d35ab4ae0c6c",
        "trajectory_sha256": "dc869c0cda073073d0d4e7ab89db262235be5b068f17c7b8971df30396381228",
        "report_sha256": "8cc8e3094188420c88f8b8ddfe7ea2593cbbe80750fe96ab42cbd5f9b04c27ec"
      }
    },
    {
      "id": "moonshotai--kimi-k3-high-pulse-seed-1",
      "model": "Kimi K3",
      "effort": "high",
      "task": "pulse",
      "seed": 1,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "4f6db42917a7427ad9a456345f6ce12e6d8a760183e6ce9f938c93aadf4345b3"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "3bc57d63901ac668fb6796155e46ae50c864d555c950c9e9dbb89d155cf36d2b",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure before experimentation; no evidence use observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice observable before failure.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback integration observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility information observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection observable.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "18efd2c984a8bbe041822aa519aa09f6752d456b7d02f05ec4179926d8e28b1f",
        "trajectory_sha256": "4f6db42917a7427ad9a456345f6ce12e6d8a760183e6ce9f938c93aadf4345b3",
        "report_sha256": "a42176a1ecb306fd9295cb7bdc7919bfaffa93bec6b3782f4974368ed4f4051f"
      }
    },
    {
      "id": "moonshotai--kimi-k3-high-pulse-seed-2",
      "model": "Kimi K3",
      "effort": "high",
      "task": "pulse",
      "seed": 2,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "ec649582ee874809b1dc74056aea9bdbd6f3e39adb7c5cef8c5d998507519c21"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "411a3986a0439b6982dd279b77dd8fba6cde8b43e643120b4b92d10fe3c1b3e8",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure before experimentation; no evidence use observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice observable before failure.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility artifacts observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection observable.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "a6ed3f5e39b1f95be19afc6a2b899aecfc0dbe6723737ae29a808d5de9856ea9",
        "trajectory_sha256": "ec649582ee874809b1dc74056aea9bdbd6f3e39adb7c5cef8c5d998507519c21",
        "report_sha256": "c412819dcd5bd80b7fa45beae89a8f986c5ee3b7d801a34d25c5dffd34d64559"
      }
    },
    {
      "id": "openai--gpt-6-astra-medium-heat-seed-0",
      "model": "GPT-6 Astra",
      "effort": "medium",
      "task": "heat",
      "seed": 0,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "First experiment: supplied task-aware ridge baseline, seed 0 and alpha 10; estab"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Trial 0 achieved person MAE 0.4899; test alpha 100 versus 10 to assess whether s"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 0.45509291999877216
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Candidate 1 is valid and has lower development person MAE: 0.4551 versus 0.4899 "
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "66842bf24ce792cbfac2759b03121c6342cf1712c473b071e01819ce958455b0"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "0aba9739e21ab0e4afaa9d5b15bf5ba8539cfe66a9b10ac66515813bfcf1f9d5",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Uses observed development MAE to motivate the next trial and compare candidates; evidence is limited to two reported results.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Establishes a baseline and tests a targeted regularization change from alpha 10 to 100; exploration is narrow.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "feedback",
              "reason": "Explicitly incorporates the first result into the next experiment and uses the improved result for selection.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00010"
              ],
              "id": "repro",
              "reason": "Provides script references, baseline seed, alpha settings, and valid execution results, but no script contents or complete execution setup.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Selects the valid candidate with lower reported development MAE and explicitly cites both results.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "e5a02709c1ec30443e341f131cc5865eb3967d28028e88bfbb89367132ed7240",
        "trajectory_sha256": "66842bf24ce792cbfac2759b03121c6342cf1712c473b071e01819ce958455b0",
        "report_sha256": "9179c6f1da59993018f9be735d9e3a2ef00c5d887d96ff215bc26219c52678f6"
      }
    },
    {
      "id": "openai--gpt-6-astra-medium-heat-seed-1",
      "model": "GPT-6 Astra",
      "effort": "medium",
      "task": "heat",
      "seed": 1,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Establish the supplied ridge baseline with seed 1 and alpha 10; evaluate person "
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Artifact must include inference.py with predict(artifact_dir, reques",
            "id": "e00004",
            "kind": "development_result",
            "primary_loss": null
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Trial 0 failed on an output-path collision, not model quality. Clear that collis"
            },
            "id": "e00005",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00009",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          },
          {
            "evidence_ids": [
              "e00004",
              "e00009"
            ],
            "id": "e00010",
            "kind": "final_selection",
            "reason": "Candidate 1 is the only valid evaluated artifact: seed-1 ridge achieved person M"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "ded642e1593e1d4c0c5090c069203ae736f4f815f3ff4d2dbb41e148634cf2a3"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "81e9b9c70908bf0d3fc6271bd18d71b374dfc910104c8d93eae89e50b06e16f6",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00004",
                "e00009",
                "e00010"
              ],
              "id": "evidence",
              "reason": "Selection uses the observed validity and loss results; the claimed output-path collision is not established by the supplied failure message.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00009"
              ],
              "id": "experiment",
              "reason": "Establishing a ridge baseline and repairing an invalid artifact are sensible steps; no model-quality comparison is shown.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00004",
                "e00005",
                "e00009"
              ],
              "id": "feedback",
              "reason": "Responded to the failed evaluation with a successful revision, although the stated diagnosis is not supported by the visible error.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00009"
              ],
              "id": "repro",
              "reason": "Seed, ridge alpha, script references, and a measured loss are recorded, but script contents and complete evaluation details are absent.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00004",
                "e00009",
                "e00010"
              ],
              "id": "selection",
              "reason": "Chose the only valid evaluated candidate and explicitly cited both evaluation outcomes, without claiming superiority over unseen alternatives.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "1b1f346642ee87dc388428f62b3581007291befb391e60cd2cec647a3f888b6e",
        "trajectory_sha256": "ded642e1593e1d4c0c5090c069203ae736f4f815f3ff4d2dbb41e148634cf2a3",
        "report_sha256": "df3b5aaaf01dfc7da2e21784f8e8ddc6514f79366b23b82166ab11a31ebe594d"
      }
    },
    {
      "id": "openai--gpt-6-astra-medium-heat-seed-2",
      "model": "GPT-6 Astra",
      "effort": "medium",
      "task": "heat",
      "seed": 2,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Establish the supplied ridge baseline with seed 2 and alpha 10; measure person M"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Artifact must include inference.py with predict(artifact_dir, reques",
            "id": "e00004",
            "kind": "development_result",
            "primary_loss": null
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Trial 0 failed before evaluation with FileExistsError. Clear the conflicting art"
            },
            "id": "e00005",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00009",
            "kind": "development_result",
            "primary_loss": 0.48989589611764356
          },
          {
            "evidence_ids": [
              "e00004",
              "e00009"
            ],
            "id": "e00010",
            "kind": "final_selection",
            "reason": "Candidate 1 is the only valid evaluated artifact: seed-2 ridge (alpha 10) achiev"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "d5ed996cd3b7e2bfa1b1f4c5b8358ce10a2a6c7a502b11ca15ccbb0e78de9921"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "0ec5bef1016623e884050deae901b3a7617d2cbe75f4e0f76c2141f9388ddeb6",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00004",
                "e00005",
                "e00009",
                "e00010"
              ],
              "id": "evidence",
              "reason": "Selection uses observed validity and loss, but the retry describes a FileExistsError rather than the reported inference-interface ValueError.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00009"
              ],
              "id": "experiment",
              "reason": "A specified ridge baseline followed by a repair produces a valid evaluation, but no comparative modeling experiment is shown.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00004",
                "e00005",
                "e00009"
              ],
              "id": "feedback",
              "reason": "The retry succeeds after failure, but its stated diagnosis does not match the supplied failure; the actual repair is not visible.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00009"
              ],
              "id": "repro",
              "reason": "Seed, alpha, script names, and evaluated loss are supplied, but executable changes and full evaluation setup are absent.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00004",
                "e00009",
                "e00010"
              ],
              "id": "selection",
              "reason": "Selects the only valid evaluated candidate and explicitly cites both results; the visible evidence supports that choice.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "70757cfbb056e5231da1cc8fc6e240cad99be324bf2f20d07d1eb16f53d3fbb4",
        "trajectory_sha256": "d5ed996cd3b7e2bfa1b1f4c5b8358ce10a2a6c7a502b11ca15ccbb0e78de9921",
        "report_sha256": "2ee2bfd621e691108826712ea19f5f8065ddaced14f67ad93ecc40d9b4444ce7"
      }
    },
    {
      "id": "openai--gpt-6-astra-medium-load-seed-0",
      "model": "GPT-6 Astra",
      "effort": "medium",
      "task": "load",
      "seed": 0,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Use the supplied ridge baseline with seed 0 and alpha 10 as the first reproducib"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 32.159375997346515
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Trial 1 achieved 32.16 W MAE. Test stronger ridge regularization (alpha 100 vs 1"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 34.866525936270556
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Candidate 0 is valid and achieved lower development person MAE: 32.16 W versus 3"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "b4def8a87e0ae21291a0ae7b160e016df84d9f11c4008f8ab2fa7b0744687176"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "aacaf637011906287c8aad6379e78593ee4ca5eb34e7e15c00b79e21b4a2ac87",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Uses measured development losses to motivate a follow-up and compare valid candidates; evidence is limited to two trials.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Establishes a baseline then tests stronger ridge regularization, a focused hyperparameter change, but explores only one alternative.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "feedback",
              "reason": "Carries the first measured loss into the next hypothesis and uses the worse follow-up result to retain the baseline.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00010"
              ],
              "id": "repro",
              "reason": "Records script references, baseline seed and alpha, follow-up alpha, and valid executions; script contents and full execution configuration are not supplied.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Explicitly selects the valid candidate with lower observed development loss and cites both supporting results.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "287883b2f451f5e9291dcc31523a166e6c5409e105b21b4ee82b9a26a8d68a46",
        "trajectory_sha256": "b4def8a87e0ae21291a0ae7b160e016df84d9f11c4008f8ab2fa7b0744687176",
        "report_sha256": "6c0f17309af44518bf6f874c42f99b1adb17f691a46c5dee4fd87e749ff2bc92"
      }
    },
    {
      "id": "openai--gpt-6-astra-medium-load-seed-1",
      "model": "GPT-6 Astra",
      "effort": "medium",
      "task": "load",
      "seed": 1,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Start with the supplied ridge baseline: regularization limits variance for unsee"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 32.159375997346515
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Ridge baseline MAE was 32.159 W. Test stronger regularization (alpha=100) for un"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": 34.866525936270556
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Candidate 0 was execution-valid and had lower development person MAE: 32.159 W v"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "f3e01c2b10b1b20ff9038be643a90565dc572a5fbf34c99b00c8c974941b8873"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "17c9e1012132e517657d32c396429a90c50a4b069bf647ed64684c90764d44ea",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "evidence",
              "reason": "Uses reported development MAE to motivate a follow-up and compare candidates; evidence is limited to two runs.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006"
              ],
              "id": "experiment",
              "reason": "Tests a baseline and a targeted stronger-regularization alternative with an explicit variance-control hypothesis.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00005",
                "e00006",
                "e00010",
                "e00011"
              ],
              "id": "feedback",
              "reason": "Carries baseline feedback into the next experiment and rejects the worse follow-up in final selection.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00006",
                "e00005",
                "e00010"
              ],
              "id": "repro",
              "reason": "Names trial files and reports execution validity, but supplies no code contents, full configuration, data split, or seeds.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005",
                "e00010",
                "e00011"
              ],
              "id": "selection",
              "reason": "Selects the execution-valid candidate with the lower reported development loss and cites both comparison results.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "d77b30bb60b8329701ca0b5569389e034dfa95acb5d1bcf20736978e986310c0",
        "trajectory_sha256": "f3e01c2b10b1b20ff9038be643a90565dc572a5fbf34c99b00c8c974941b8873",
        "report_sha256": "37fed6500416c3bdbd6790dbeff0f8b37c816ba347f02d16e3e21b83123498f0"
      }
    },
    {
      "id": "openai--gpt-6-astra-medium-load-seed-2",
      "model": "GPT-6 Astra",
      "effort": "medium",
      "task": "load",
      "seed": 2,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Experiment 1: supplied ridge helper with alpha=10 and seed=2; a regularized base"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Artifact must include inference.py with predict(artifact_dir, reques",
            "id": "e00004",
            "kind": "development_result",
            "primary_loss": null
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "4c52db771163948e6d060deb58182a655a07dd15aa3229b09c765092cb043ab0"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "2b12e49c43e4ccabeda31bfaa331946ec5edd12e2c3109e1a23729f4785acaf1",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00001"
              ],
              "id": "evidence",
              "reason": "References the supplied ridge helper, but provides no data analysis or empirical support for the choice.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00001",
                "e00004"
              ],
              "id": "experiment",
              "reason": "Defines a reasonable regularized baseline with explicit alpha and seed, but the run fails artifact validation and yields no loss.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00004"
              ],
              "id": "feedback",
              "reason": "Validation feedback is present, but no subsequent response or revision is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "e00001",
                "e00004"
              ],
              "id": "repro",
              "reason": "Records a code filename and key parameters, but the required inference interface is missing and execution is invalid.",
              "score": 1
            },
            {
              "evidence_ids": [],
              "id": "selection",
              "reason": "No final selection or comparison is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "8d2bffb0da8d7945f0aee3365764e8d9f9b3ab8c5d242c23b4ede11165d3392b",
        "trajectory_sha256": "4c52db771163948e6d060deb58182a655a07dd15aa3229b09c765092cb043ab0",
        "report_sha256": "a5f828512b6680a02b943e30816d21d5af7526e12e78869f31dbbec2aedeea06"
      }
    },
    {
      "id": "openai--gpt-6-astra-medium-pulse-seed-0",
      "model": "GPT-6 Astra",
      "effort": "medium",
      "task": "pulse",
      "seed": 0,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Evaluate the supplied ridge baseline with alpha=10 and seed 0; regularization is"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Artifact must include inference.py with predict(artifact_dir, reques",
            "id": "e00004",
            "kind": "development_result",
            "primary_loss": null
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Repair trial 0's artifact-path collision, then evaluate the supplied ridge basel"
            },
            "id": "e00005",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00009",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          },
          {
            "evidence_ids": [
              "e00004",
              "e00009"
            ],
            "id": "e00010",
            "kind": "final_selection",
            "reason": "Candidate 1 is the only valid evaluated artifact: seed-0 ridge with alpha=10 ach"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "ee726511e4b18f53ae46a9ba5251d38ce5375dc02b239de8071f13ea942e39fb"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "5374c4ef72bb34beedd5b1609409199605eb2e7d61525339633e65b9b3f51dbb",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00004",
                "e00009",
                "e00010"
              ],
              "id": "evidence",
              "reason": "Selection cites the failed and successful evaluations and distinguishes artifact validity; evidence is limited to one valid loss.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "experiment",
              "reason": "Tests a specified ridge baseline and then repairs its artifact packaging, but shows no comparative modeling experiment.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00004",
                "e00005",
                "e00009"
              ],
              "id": "feedback",
              "reason": "Responds to the artifact failure with a targeted repair, followed by a valid evaluation.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00009"
              ],
              "id": "repro",
              "reason": "Records script references, alpha, seed, and evaluation loss, but supplied evidence lacks executable contents and full reproduction details.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00004",
                "e00009",
                "e00010"
              ],
              "id": "selection",
              "reason": "Chooses the only valid evaluated artifact and explicitly cites the evaluation evidence; this is justified within the supplied candidate set.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "07bffe1fe8fdf361b98bbb21ed5ada82aefe3713a5b534257eb1a7ddc0a55805",
        "trajectory_sha256": "ee726511e4b18f53ae46a9ba5251d38ce5375dc02b239de8071f13ea942e39fb",
        "report_sha256": "8de554498183b03b1dfc78f2d57d016e402fccd603a4f4c8888e8b356ed513a3"
      }
    },
    {
      "id": "openai--gpt-6-astra-medium-pulse-seed-1",
      "model": "GPT-6 Astra",
      "effort": "medium",
      "task": "pulse",
      "seed": 1,
      "execution_valid": true,
      "status": "missing",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Establish the supplied ridge baseline with seed 1 and alpha 10; evaluate unseen-"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Baseline ridge alpha=10 achieved 12.934 person MAE. Test alpha=100 with seed 1 t"
            },
            "id": "e00006",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Artifact must include inference.py with predict(artifact_dir, reques",
            "id": "e00010",
            "kind": "development_result",
            "primary_loss": null
          },
          {
            "evidence_ids": [
              "e00005",
              "e00010"
            ],
            "id": "e00011",
            "kind": "final_selection",
            "reason": "Candidate 0 is the only valid evaluated artifact: ridge alpha=10, seed 1 achieve"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "86979d2015a252d337dd9b4e6e13ac9c80f4ae88d953bfdf02cb69731be15ae4"
      },
      "report": null,
      "provenance": {
        "receipt_sha256": "f70dd1807c3af9df74d8275bf3509c5f6e44e91e86428100ece2abe594c89745",
        "trajectory_sha256": "86979d2015a252d337dd9b4e6e13ac9c80f4ae88d953bfdf02cb69731be15ae4",
        "report_sha256": null
      }
    },
    {
      "id": "openai--gpt-6-astra-medium-pulse-seed-2",
      "model": "GPT-6 Astra",
      "effort": "medium",
      "task": "pulse",
      "seed": 2,
      "execution_valid": true,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Experiment 1: supplied ridge baseline with alpha=10 and seed 2; establishes an o"
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Artifact must include inference.py with predict(artifact_dir, reques",
            "id": "e00004",
            "kind": "development_result",
            "primary_loss": null
          },
          {
            "decision": {
              "code_diff": "trial1.py",
              "hypothesis": "Retries the supplied seed-2 ridge baseline in a fresh output path to avoid exper"
            },
            "id": "e00005",
            "kind": "experiment"
          },
          {
            "execution_valid": true,
            "failure_reason": null,
            "id": "e00009",
            "kind": "development_result",
            "primary_loss": 12.933832525744398
          },
          {
            "evidence_ids": [
              "e00004",
              "e00009"
            ],
            "id": "e00010",
            "kind": "final_selection",
            "reason": "Candidate 1 is the only valid evaluated artifact: seed-2 ridge with alpha=10 ach"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "a9255f0230ca8e0f594d78a04a7ca494ef6e08d3e88a59a278bb364acd6ecaf1"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "f22c4a924c2bcb703b6ba2bcfe2a07711cb3c751a23710d6379d1680e943fbe0",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00004",
                "e00009",
                "e00010"
              ],
              "id": "evidence",
              "reason": "Selection uses observed validity and development loss, but evidence is limited to one valid baseline.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005"
              ],
              "id": "experiment",
              "reason": "Establishes a ridge baseline and retries it; no comparative modeling or hyperparameter experiment is shown.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00004",
                "e00005",
                "e00009"
              ],
              "id": "feedback",
              "reason": "Retries after the artifact-interface failure and obtains a valid evaluation; the precise repair is not supplied.",
              "score": 3
            },
            {
              "evidence_ids": [
                "e00001",
                "e00005",
                "e00009"
              ],
              "id": "repro",
              "reason": "Records trial filenames, seed, alpha, and an evaluation result, but supplies neither executable code nor full reproduction details.",
              "score": 2
            },
            {
              "evidence_ids": [
                "e00004",
                "e00009",
                "e00010"
              ],
              "id": "selection",
              "reason": "Chooses the only valid evaluated artifact and explicitly cites both evaluation outcomes; no unsupported comparative claim is shown.",
              "score": 4
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "2df0615693a30c5451f67bedb6edc8d9d4e288b40cb6b82b48fe815b152de1d4",
        "trajectory_sha256": "a9255f0230ca8e0f594d78a04a7ca494ef6e08d3e88a59a278bb364acd6ecaf1",
        "report_sha256": "7f6250c0f3b360d485b96e08efe9640e78362de4d5a4b684e7557a25ec948470"
      }
    },
    {
      "id": "x-ai--grok-4-7-medium-heat-seed-0",
      "model": "Grok 4.7",
      "effort": "medium",
      "task": "heat",
      "seed": 0,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Need data layout and baseline API before writing experiment 1 training code."
            },
            "id": "e00002",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Missing artifact",
            "id": "e00005",
            "kind": "development_result",
            "primary_loss": null
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "ce10ef469882e9dfb35e04be244792425b5929fa2fa029c779494e9373598e84"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "67606a7d2323678a8e8bbe146f9bb04a569e5553878f20ece6ddc9cfa221b546",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00002"
              ],
              "id": "evidence",
              "reason": "Identifies needed data-layout and API information, but cites no observations supporting the decision.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00002"
              ],
              "id": "experiment",
              "reason": "States a preparatory need rather than a testable hypothesis or defined experimental comparison.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00005"
              ],
              "id": "feedback",
              "reason": "Failure feedback is present, but no subsequent response to it is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "e00002",
                "e00005"
              ],
              "id": "repro",
              "reason": "The referenced artifact is missing; execution is invalid and produces no loss.",
              "score": 0
            },
            {
              "evidence_ids": [],
              "id": "selection",
              "reason": "No final selection is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "b055da454c09dce21bd82088f432d8b4bffcf5d4baff3743f5b16f9c7cc0890c",
        "trajectory_sha256": "ce10ef469882e9dfb35e04be244792425b5929fa2fa029c779494e9373598e84",
        "report_sha256": "312b60bdd174b87c2d247c428100fb1aef6e4af7d058036a04d3fb178d37ee25"
      }
    },
    {
      "id": "x-ai--grok-4-7-medium-heat-seed-1",
      "model": "Grok 4.7",
      "effort": "medium",
      "task": "heat",
      "seed": 1,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "40061fcf62eb5615e91c887b152932844d26f257024d2c1e28a3addd8616f12c"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "e3ade654d6054eb588191415ecee783bb6e0b9384c69264648f9da3b5369d998",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure before experimentation; no evidence use observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback integration observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No reproducible procedure or experiment observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection observable.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "4cd6498c2704c67ee6865330b650ae8f9195bfa50cffd6f7d06122bdc3228290",
        "trajectory_sha256": "40061fcf62eb5615e91c887b152932844d26f257024d2c1e28a3addd8616f12c",
        "report_sha256": "6e744e3e466ec8f365d8fa9035b3a3074d8b823ad2bcc1c515f313ad3c2fbe05"
      }
    },
    {
      "id": "x-ai--grok-4-7-medium-heat-seed-2",
      "model": "Grok 4.7",
      "effort": "medium",
      "task": "heat",
      "seed": 2,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "43064fd1b9c9671e83202886f958bcc16bc8b60ba541f7958d59d80c258a84e5"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "a56548ad34127b4e39de366849dd61ae8946c739433134592879a941033c81b7",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure occurred before experimentation; no evidence use is observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No reproducible procedure or experimental artifacts are supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "526edc0484a1bd1f48225be5b0267195d6150f6c1130fd71ead7f275e27f8f95",
        "trajectory_sha256": "43064fd1b9c9671e83202886f958bcc16bc8b60ba541f7958d59d80c258a84e5",
        "report_sha256": "ea1780fdc8f5f1311b0e1cc23070bf43fb2e74959162d1ed523220fad197e067"
      }
    },
    {
      "id": "x-ai--grok-4-7-medium-load-seed-0",
      "model": "Grok 4.7",
      "effort": "medium",
      "task": "load",
      "seed": 0,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "9236cc281afd8647a95f07f5d6781bda286d932fab479fd1d8b400e35314188d"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "e34cd5a9926b284def6d11bc441b3ed1be6e67ecded493d85ceba6960614ef36",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure before experimentation leaves evidence use unobservable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility evidence is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "fd7c031aa44e4ace8a5ed55fb1bdb93db59bd085d6e874bc912e8fe7c7d02baa",
        "trajectory_sha256": "9236cc281afd8647a95f07f5d6781bda286d932fab479fd1d8b400e35314188d",
        "report_sha256": "1cdf4373f5d47084f9ae77d95becb0f9b3d1bdd4cc532f77527371de47276717"
      }
    },
    {
      "id": "x-ai--grok-4-7-medium-load-seed-1",
      "model": "Grok 4.7",
      "effort": "medium",
      "task": "load",
      "seed": 1,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "bf65fa637cfbdcf46d17de4fc2f92e3b1a641b38f2b8255f710bb69428ddf96e"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "6567c83555e58307ec2cc2c6e01b3665c842b78d446bf2cd01d812e0fb439baa",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failed before experiment; evidence use is unobservable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No reproducible experimental procedure is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "a84a2e9d059cc414baca482d264518639b30fc0ad48d990a09ced3581bb6b1b3",
        "trajectory_sha256": "bf65fa637cfbdcf46d17de4fc2f92e3b1a641b38f2b8255f710bb69428ddf96e",
        "report_sha256": "b095b3e62a25223566a9c8e85f726a91360714a2721d9fb053dcaa94a33b8a9d"
      }
    },
    {
      "id": "x-ai--grok-4-7-medium-load-seed-2",
      "model": "Grok 4.7",
      "effort": "medium",
      "task": "load",
      "seed": 2,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "83bc8ac807654af94b58e0a7397259511924c34d94badd6a772846115931c785"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "f25405439f2f7513c26f1bf09487176bf09064f91c23164ecb3577fa8a3e0aca",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failed before experiment; evidence use is unobservable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility artifacts are supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "2cbf4a4c231eefb55fbbc1ac0e5617b20f1c06e58c421a01f7ffa13db0038417",
        "trajectory_sha256": "83bc8ac807654af94b58e0a7397259511924c34d94badd6a772846115931c785",
        "report_sha256": "13ebd98063b3cee7fd6dd5f84611327c3c5694b57b8a15a477c8887349be624f"
      }
    },
    {
      "id": "x-ai--grok-4-7-medium-pulse-seed-0",
      "model": "Grok 4.7",
      "effort": "medium",
      "task": "pulse",
      "seed": 0,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "decision": {
              "code_diff": "trial0.py",
              "hypothesis": "Exploring task files and baseline before writing experiment 1."
            },
            "id": "e00001",
            "kind": "experiment"
          },
          {
            "execution_valid": false,
            "failure_reason": "ValueError: Missing artifact",
            "id": "e00004",
            "kind": "development_result",
            "primary_loss": null
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "928f81bc5fc2c24bbd1a9173e83bafe6b6b11a4be9ccb3cba6cf1df293c4079a"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "1c158b4cd703276d8b7a82aa593e86f8c4951e03e539f605033e70c80364eade",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "e00001"
              ],
              "id": "evidence",
              "reason": "Mentions exploring task files and baseline, but supplies no findings or evidence supporting the decision.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00001",
                "e00004"
              ],
              "id": "experiment",
              "reason": "Only a generic exploration hypothesis is supplied; the attempted execution fails with a missing artifact and yields no measurement.",
              "score": 1
            },
            {
              "evidence_ids": [
                "e00004"
              ],
              "id": "feedback",
              "reason": "Failure feedback is present, but no subsequent response or revision is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "e00001",
                "e00004"
              ],
              "id": "repro",
              "reason": "A script filename is given without contents or execution details, and the required artifact is missing.",
              "score": 0
            },
            {
              "evidence_ids": [],
              "id": "selection",
              "reason": "No final selection is supplied.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "57e716195a6f0c57d53d0749cb55d95a4630d99028bdd85fbcf022f0f0043c6b",
        "trajectory_sha256": "928f81bc5fc2c24bbd1a9173e83bafe6b6b11a4be9ccb3cba6cf1df293c4079a",
        "report_sha256": "f073a7c2536ed337a9255b3bc3c4cca6be553539a1df37aa46e02357b3374969"
      }
    },
    {
      "id": "x-ai--grok-4-7-medium-pulse-seed-1",
      "model": "Grok 4.7",
      "effort": "medium",
      "task": "pulse",
      "seed": 1,
      "execution_valid": false,
      "status": "missing",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "18909d2a281fb6b12827406f26ac8d83988410b3ff78714798aca41dc6bb9c8e"
      },
      "report": null,
      "provenance": {
        "receipt_sha256": "e8701f210a8a6a145c849bd652c2485cacf5e6d5d1f4b6b8ef8d7e13267dc702",
        "trajectory_sha256": "18909d2a281fb6b12827406f26ac8d83988410b3ff78714798aca41dc6bb9c8e",
        "report_sha256": null
      }
    },
    {
      "id": "x-ai--grok-4-7-medium-pulse-seed-2",
      "model": "Grok 4.7",
      "effort": "medium",
      "task": "pulse",
      "seed": 2,
      "execution_valid": false,
      "status": "reviewed",
      "packet": {
        "events": [
          {
            "id": "no-evidence",
            "kind": "failed_before_experiment"
          }
        ],
        "rubric": "compact-process-v1",
        "trajectory_sha256": "bdd772d1bd8c23f6a9eb0fa5483b69775b4d8dc39d597a1e0a6efbc6b8d2a7a7"
      },
      "report": {
        "judge_configuration_sha256": "ea064c3ae28dbd524d2d486f91a2fa015d2e04dec7e283840b07164ed93fc432",
        "packet_sha256": "e43a7da7b2a56238063302677fd8253ec5e5833e45b597f4bfef9b5a93e29da0",
        "verdict": {
          "criteria": [
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "evidence",
              "reason": "Failure before experimentation provides no observable evidence use.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "experiment",
              "reason": "No experiment choice is observable before failure.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "feedback",
              "reason": "No feedback or integration is observable.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "repro",
              "reason": "No experimental procedure or reproducibility information is supplied.",
              "score": null
            },
            {
              "evidence_ids": [
                "no-evidence"
              ],
              "id": "selection",
              "reason": "No final selection is observable.",
              "score": null
            }
          ]
        }
      },
      "provenance": {
        "receipt_sha256": "a1069f1c8cc08b7ff6ac4d5685fbb720b7e3493a7012f96bd7e78d10deaf3d13",
        "trajectory_sha256": "bdd772d1bd8c23f6a9eb0fa5483b69775b4d8dc39d597a1e0a6efbc6b8d2a7a7",
        "report_sha256": "684b35d0169ca4085f99d04cde6d37a8470e68f9cff5aa30ffc80d2033d9d34b"
      }
    }
  ]
}
