metrics.json

{
  "per_head": {
    "complexity": {
      "accuracy": 0.6954,
      "macro_f1": 0.7011,
      "per_label": {
        "easy": {
          "precision": 0.7258,
          "recall": 0.75,
          "f1": 0.7377,
          "support": 60
        },
        "medium": {
          "precision": 0.6232,
          "recall": 0.6418,
          "f1": 0.6324,
          "support": 67
        },
        "hard": {
          "precision": 0.7674,
          "recall": 0.7021,
          "f1": 0.7333,
          "support": 47
        }
      },
      "confusion_matrix": [
        [
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        ],
        [
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          10
        ],
        [
          3,
          11,
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        ]
      ]
    },
    "task_type": {
      "accuracy": 0.9138,
      "macro_f1": 0.9093,
      "per_label": {
        "bugfix": {
          "precision": 0.9565,
          "recall": 0.88,
          "f1": 0.9167,
          "support": 25
        },
        "feature": {
          "precision": 0.9302,
          "recall": 0.9524,
          "f1": 0.9412,
          "support": 42
        },
        "refactor": {
          "precision": 0.8696,
          "recall": 0.9524,
          "f1": 0.9091,
          "support": 21
        },
        "test": {
          "precision": 1.0,
          "recall": 0.8571,
          "f1": 0.9231,
          "support": 14
        },
        "design": {
          "precision": 0.9375,
          "recall": 0.9375,
          "f1": 0.9375,
          "support": 16
        },
        "docs": {
          "precision": 0.9333,
          "recall": 0.9333,
          "f1": 0.9333,
          "support": 15
        },
        "migration": {
          "precision": 0.9167,
          "recall": 1.0,
          "f1": 0.9565,
          "support": 22
        },
        "exploration": {
          "precision": 0.7778,
          "recall": 0.7368,
          "f1": 0.7568,
          "support": 19
        }
      },
      "confusion_matrix": [
        [
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        ],
        [
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        [
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        [
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        [
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        [
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        [
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        ]
      ]
    },
    "risk": {
      "accuracy": 0.6954,
      "macro_f1": 0.6554,
      "per_label": {
        "low": {
          "precision": 0.8,
          "recall": 0.8276,
          "f1": 0.8136,
          "support": 87
        },
        "medium": {
          "precision": 0.5333,
          "recall": 0.6038,
          "f1": 0.5664,
          "support": 53
        },
        "high": {
          "precision": 0.7083,
          "recall": 0.5,
          "f1": 0.5862,
          "support": 34
        }
      },
      "confusion_matrix": [
        [
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          13,
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        ],
        [
          16,
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        ],
        [
          2,
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        ]
      ]
    }
  },
  "overall": {
    "exact_match": 0.4655,
    "macro_average_f1": 0.7553,
    "automation_safe_accuracy": 0.6935,
    "automation_safe_coverage": 0.3563,
    "confidence_threshold": 0.8,
    "confidence_calibration": {
      "ece": 0.303072,
      "bins": [
        {
          "range": [
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          ],
          "count": 5,
          "avg_confidence": 0.586,
          "accuracy": 0.0
        },
        {
          "range": [
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          ],
          "count": 48,
          "avg_confidence": 0.6575,
          "accuracy": 0.2917
        },
        {
          "range": [
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          ],
          "count": 59,
          "avg_confidence": 0.7473,
          "accuracy": 0.4068
        },
        {
          "range": [
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          ],
          "count": 33,
          "avg_confidence": 0.8512,
          "accuracy": 0.5758
        },
        {
          "range": [
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          ],
          "count": 29,
          "avg_confidence": 0.9333,
          "accuracy": 0.8276
        }
      ]
    }
  },
  "temperature_scaling": {
    "method": "per_head_temperature_scaling",
    "per_head": {
      "complexity": 0.891251,
      "task_type": 0.707946,
      "risk": 1.059254
    }
  },
  "complexity_subdims": {
    "reasoning_depth": {
      "mae": 0.1069,
      "r2": 0.5888
    },
    "spec_completeness": {
      "mae": 0.1033,
      "r2": 0.3667
    },
    "scope_breadth": {
      "mae": 0.1076,
      "r2": 0.5044
    },
    "domain_knowledge": {
      "mae": 0.1036,
      "r2": 0.4405
    }
  },
  "risk_subdims": {
    "security_surface": {
      "mae": 0.1517,
      "r2": 0.1937
    },
    "data_sensitivity": {
      "mae": 0.1184,
      "r2": 0.3094
    },
    "production_exposure": {
      "mae": 0.1182,
      "r2": 0.6323
    },
    "reversal_cost": {
      "mae": 0.1045,
      "r2": 0.6316
    }
  }
}