{
  "topic": "long_horizon",
  "round": 3,
  "method_name": "temporal utility window",
  "idea": "Combine dimension evidence with utility drops, fast swipes, and delayed-feedback timing.",
  "diagnosed_issue": "Long-horizon round 3 dominant issue: culprit_dimension_evidence_gap.",
  "patch_for_next_round": "Fuse delayed-feedback dimension tokens with per-turn feature tags, severity, and repairability.",
  "patch_source": "autodiagnosed",
  "auto_diagnosis": {
    "dominant_failure_mode": "culprit_dimension_evidence_gap",
    "evidence": {
      "step_miss": 5,
      "dimension_miss": 5,
      "low_rank_gold": 0
    },
    "diagnosis_text": "Long-horizon round 3 dominant issue: culprit_dimension_evidence_gap.",
    "selected_next_patch": "Fuse delayed-feedback dimension tokens with per-turn feature tags, severity, and repairability."
  },
  "selected_next_patch": "Fuse delayed-feedback dimension tokens with per-turn feature tags, severity, and repairability.",
  "comparison_to_previous": {
    "status": "improved",
    "primary_metric": "credit_calibration",
    "primary_delta": 0.2803,
    "headline": "credit_calibration changed +0.2803 vs previous round."
  },
  "failure_examples": [
    {
      "episode_id": "trace_0008",
      "delayed_comment": "那个误会梗埋得太早，后面解释让我出戏。",
      "gold_step": 4,
      "predicted_step": 2,
      "gold_dimension": "trope_misunderstanding",
      "predicted_dimension": "female_agency",
      "top_candidates": [
        {
          "step": 2,
          "score": 2.9202,
          "reason": "tag:female_agency+text+tag:trope_misunderstanding+temporal_window",
          "tags": [
            "female_agency",
            "trope_misunderstanding"
          ]
        },
        {
          "step": 4,
          "score": 2.8021,
          "reason": "text+tag:trope_misunderstanding+fast_swipe+temporal_window",
          "tags": [
            "trope_misunderstanding"
          ]
        },
        {
          "step": 5,
          "score": 0.73,
          "reason": "tag:pacing+temporal_window",
          "tags": [
            "pacing"
          ]
        }
      ],
      "problems": [
        "step_miss:gold=4:pred=2",
        "dimension_miss:gold=trope_misunderstanding:pred=female_agency"
      ],
      "severity": 2.7
    },
    {
      "episode_id": "trace_0017",
      "delayed_comment": "前面设定解释太密，后面节奏被拖住了。",
      "gold_step": 6,
      "predicted_step": 4,
      "gold_dimension": "lore_density",
      "predicted_dimension": "female_agency",
      "top_candidates": [
        {
          "step": 4,
          "score": 3.389,
          "reason": "tag:female_agency+text+tag:lore_density+fast_swipe+temporal_window",
          "tags": [
            "female_agency",
            "lore_density"
          ]
        },
        {
          "step": 6,
          "score": 2.9512,
          "reason": "text+tag:lore_density+fast_swipe+temporal_window",
          "tags": [
            "lore_density"
          ]
        },
        {
          "step": 5,
          "score": 0.3,
          "reason": "temporal_window",
          "tags": []
        }
      ],
      "problems": [
        "step_miss:gold=6:pred=4",
        "dimension_miss:gold=lore_density:pred=female_agency"
      ],
      "severity": 2.7
    },
    {
      "episode_id": "trace_0034",
      "delayed_comment": "前面设定解释太密，后面节奏被拖住了。",
      "gold_step": 4,
      "predicted_step": 2,
      "gold_dimension": "lore_density",
      "predicted_dimension": "female_agency",
      "top_candidates": [
        {
          "step": 2,
          "score": 2.6219,
          "reason": "tag:female_agency+text+tag:lore_density+temporal_window",
          "tags": [
            "female_agency",
            "lore_density"
          ]
        },
        {
          "step": 4,
          "score": 2.1,
          "reason": "text+tag:lore_density+temporal_window",
          "tags": [
            "lore_density"
          ]
        },
        {
          "step": 3,
          "score": 0.8,
          "reason": "tag:pacing+temporal_window",
          "tags": [
            "pacing"
          ]
        }
      ],
      "problems": [
        "step_miss:gold=4:pred=2",
        "dimension_miss:gold=lore_density:pred=female_agency"
      ],
      "severity": 2.7
    },
    {
      "episode_id": "trace_0050",
      "delayed_comment": "那个误会梗埋得太早，后面解释让我出戏。",
      "gold_step": 2,
      "predicted_step": 1,
      "gold_dimension": "trope_misunderstanding",
      "predicted_dimension": "pacing",
      "top_candidates": [
        {
          "step": 1,
          "score": 2.4786,
          "reason": "tag:pacing+text+tag:trope_misunderstanding+temporal_window",
          "tags": [
            "pacing",
            "trope_misunderstanding"
          ]
        },
        {
          "step": 2,
          "score": 2.2634,
          "reason": "text+tag:trope_misunderstanding+temporal_window",
          "tags": [
            "trope_misunderstanding"
          ]
        },
        {
          "step": 5,
          "score": 0.3801,
          "reason": "temporal_window",
          "tags": []
        }
      ],
      "problems": [
        "step_miss:gold=2:pred=1",
        "dimension_miss:gold=trope_misunderstanding:pred=pacing"
      ],
      "severity": 2.7
    },
    {
      "episode_id": "trace_0094",
      "delayed_comment": "前面设定解释太密，后面节奏被拖住了。",
      "gold_step": 5,
      "predicted_step": 3,
      "gold_dimension": "lore_density",
      "predicted_dimension": "female_agency",
      "top_candidates": [
        {
          "step": 3,
          "score": 2.8963,
          "reason": "tag:female_agency+text+tag:lore_density+temporal_window",
          "tags": [
            "female_agency",
            "lore_density"
          ]
        },
        {
          "step": 5,
          "score": 2.1,
          "reason": "text+tag:lore_density+temporal_window",
          "tags": [
            "lore_density"
          ]
        },
        {
          "step": 7,
          "score": 1.0523,
          "reason": "tag:female_agency+temporal_window",
          "tags": [
            "female_agency"
          ]
        }
      ],
      "problems": [
        "step_miss:gold=5:pred=3",
        "dimension_miss:gold=lore_density:pred=female_agency"
      ],
      "severity": 2.7
    }
  ],
  "concrete_problems": [
    {
      "episode_id": "trace_0008",
      "delayed_comment": "那个误会梗埋得太早，后面解释让我出戏。",
      "gold_step": 4,
      "predicted_step": 2,
      "gold_dimension": "trope_misunderstanding",
      "predicted_dimension": "female_agency",
      "top_candidates": [
        {
          "step": 2,
          "score": 2.9202,
          "reason": "tag:female_agency+text+tag:trope_misunderstanding+temporal_window",
          "tags": [
            "female_agency",
            "trope_misunderstanding"
          ]
        },
        {
          "step": 4,
          "score": 2.8021,
          "reason": "text+tag:trope_misunderstanding+fast_swipe+temporal_window",
          "tags": [
            "trope_misunderstanding"
          ]
        },
        {
          "step": 5,
          "score": 0.73,
          "reason": "tag:pacing+temporal_window",
          "tags": [
            "pacing"
          ]
        }
      ],
      "problems": [
        "step_miss:gold=4:pred=2",
        "dimension_miss:gold=trope_misunderstanding:pred=female_agency"
      ],
      "severity": 2.7
    },
    {
      "episode_id": "trace_0017",
      "delayed_comment": "前面设定解释太密，后面节奏被拖住了。",
      "gold_step": 6,
      "predicted_step": 4,
      "gold_dimension": "lore_density",
      "predicted_dimension": "female_agency",
      "top_candidates": [
        {
          "step": 4,
          "score": 3.389,
          "reason": "tag:female_agency+text+tag:lore_density+fast_swipe+temporal_window",
          "tags": [
            "female_agency",
            "lore_density"
          ]
        },
        {
          "step": 6,
          "score": 2.9512,
          "reason": "text+tag:lore_density+fast_swipe+temporal_window",
          "tags": [
            "lore_density"
          ]
        },
        {
          "step": 5,
          "score": 0.3,
          "reason": "temporal_window",
          "tags": []
        }
      ],
      "problems": [
        "step_miss:gold=6:pred=4",
        "dimension_miss:gold=lore_density:pred=female_agency"
      ],
      "severity": 2.7
    },
    {
      "episode_id": "trace_0034",
      "delayed_comment": "前面设定解释太密，后面节奏被拖住了。",
      "gold_step": 4,
      "predicted_step": 2,
      "gold_dimension": "lore_density",
      "predicted_dimension": "female_agency",
      "top_candidates": [
        {
          "step": 2,
          "score": 2.6219,
          "reason": "tag:female_agency+text+tag:lore_density+temporal_window",
          "tags": [
            "female_agency",
            "lore_density"
          ]
        },
        {
          "step": 4,
          "score": 2.1,
          "reason": "text+tag:lore_density+temporal_window",
          "tags": [
            "lore_density"
          ]
        },
        {
          "step": 3,
          "score": 0.8,
          "reason": "tag:pacing+temporal_window",
          "tags": [
            "pacing"
          ]
        }
      ],
      "problems": [
        "step_miss:gold=4:pred=2",
        "dimension_miss:gold=lore_density:pred=female_agency"
      ],
      "severity": 2.7
    },
    {
      "episode_id": "trace_0050",
      "delayed_comment": "那个误会梗埋得太早，后面解释让我出戏。",
      "gold_step": 2,
      "predicted_step": 1,
      "gold_dimension": "trope_misunderstanding",
      "predicted_dimension": "pacing",
      "top_candidates": [
        {
          "step": 1,
          "score": 2.4786,
          "reason": "tag:pacing+text+tag:trope_misunderstanding+temporal_window",
          "tags": [
            "pacing",
            "trope_misunderstanding"
          ]
        },
        {
          "step": 2,
          "score": 2.2634,
          "reason": "text+tag:trope_misunderstanding+temporal_window",
          "tags": [
            "trope_misunderstanding"
          ]
        },
        {
          "step": 5,
          "score": 0.3801,
          "reason": "temporal_window",
          "tags": []
        }
      ],
      "problems": [
        "step_miss:gold=2:pred=1",
        "dimension_miss:gold=trope_misunderstanding:pred=pacing"
      ],
      "severity": 2.7
    },
    {
      "episode_id": "trace_0094",
      "delayed_comment": "前面设定解释太密，后面节奏被拖住了。",
      "gold_step": 5,
      "predicted_step": 3,
      "gold_dimension": "lore_density",
      "predicted_dimension": "female_agency",
      "top_candidates": [
        {
          "step": 3,
          "score": 2.8963,
          "reason": "tag:female_agency+text+tag:lore_density+temporal_window",
          "tags": [
            "female_agency",
            "lore_density"
          ]
        },
        {
          "step": 5,
          "score": 2.1,
          "reason": "text+tag:lore_density+temporal_window",
          "tags": [
            "lore_density"
          ]
        },
        {
          "step": 7,
          "score": 1.0523,
          "reason": "tag:female_agency+temporal_window",
          "tags": [
            "female_agency"
          ]
        }
      ],
      "problems": [
        "step_miss:gold=5:pred=3",
        "dimension_miss:gold=lore_density:pred=female_agency"
      ],
      "severity": 2.7
    }
  ],
  "data_eval_spec": {
    "dataset_name": "TRACE-USER-Bench synthetic delayed-feedback traces",
    "data_schema": "One row per multi-turn episode: turn trace, utility/implicit feedback, delayed comment, gold culprit step/dimension, counterfactual repairs.",
    "evaluation_protocol": "Rank culprit steps from the full trace, compare top prediction and reciprocal rank to gold, then estimate counterfactual repair gain and confidence calibration.",
    "metric_definitions": {
      "culprit_step_accuracy": "Exact-match accuracy for the delayed-feedback culprit step.",
      "culprit_dimension_accuracy": "Accuracy for the causal preference/content dimension.",
      "credit_mrr": "Mean reciprocal rank of the gold culprit step.",
      "repair_gain": "Mean expected utility gain from the selected counterfactual repair.",
      "credit_calibration": "One minus confidence error; higher means confidence tracks correctness."
    },
    "sample_count": 120,
    "metrics": {
      "culprit_step_accuracy": "Exact-match accuracy for the delayed-feedback culprit step.",
      "culprit_dimension_accuracy": "Accuracy for the causal preference/content dimension.",
      "credit_mrr": "Mean reciprocal rank of the gold culprit step.",
      "repair_gain": "Mean expected utility gain from the selected counterfactual repair.",
      "credit_calibration": "One minus confidence error; higher means confidence tracks correctness."
    },
    "splits": {
      "culprit_dimensions": {
        "lore_density": 27,
        "pacing": 35,
        "trope_misunderstanding": 32,
        "female_agency": 26
      }
    }
  },
  "metrics": {
    "round": 3,
    "culprit_step_accuracy": 0.925,
    "culprit_dimension_accuracy": 0.9333,
    "credit_mrr": 0.9625,
    "repair_gain": 0.1846,
    "counterfactual_repair_gain": 0.1846,
    "credit_calibration": 0.908
  },
  "previous_metrics": {
    "round": 2,
    "culprit_step_accuracy": 0.65,
    "culprit_dimension_accuracy": 0.8917,
    "credit_mrr": 0.8167,
    "repair_gain": 0.1461,
    "counterfactual_repair_gain": 0.1461,
    "credit_calibration": 0.6277
  },
  "metric_deltas": {
    "culprit_step_accuracy": 0.275,
    "culprit_dimension_accuracy": 0.04159999999999997,
    "credit_mrr": 0.14580000000000004,
    "repair_gain": 0.03849999999999998,
    "counterfactual_repair_gain": 0.03849999999999998,
    "credit_calibration": 0.2803
  }
}