thresholds.json

{
  "schema_version": "1.0.0",
  "taxonomy_version": "1.0.0",
  "default_policy": "balanced",
  "calibration_status": "uncalibrated",
  "calibration_note": "Scores are raw softmax maxima for model spans and a fixed confidence table for rule spans. They are NOT calibrated probabilities: a span scored 0.90 does not mean it is correct 90% of the time. Per-type calibration is planned, not shipped. Choose a policy by measured precision/recall in models/evaluation.json, not by reading a score as a probability.",
  "policies": {
    "strict": {
      "score_threshold": 0.5,
      "intent": "Favour recall. Use when a human reviews every result."
    },
    "balanced": {
      "score_threshold": 0.75,
      "intent": "Default. The published per-type results in evaluation.json are measured at this threshold."
    },
    "precision": {
      "score_threshold": 0.9,
      "intent": "Favour precision. Use when a false positive is more costly than a miss."
    }
  },
  "per_type_overrides": {},
  "rule_confidence": {
    "note": "Deterministic recognizers emit a fixed confidence by evidence strength, not a learned score.",
    "checksum_validated": 0.99,
    "format_and_context": 0.97,
    "format_only": 0.93,
    "weak_format_with_context": 0.8
  }
}