target_policy.json

{
  "applies_to": "continuous rows in train and validation_ranking",
  "binary_targets": "pooled_realized_L3_L4_L5_continuous_training_pairs_by_source",
  "formula": "sigmoid((threshold_sd - standardized_canonical_value_difference) / temperature)",
  "geometry_and_calibration": "geometry and SD unchanged; binary table refitted",
  "sampling_policy": {
    "binary_probabilities": "pooled_realized_L3_L4_L5_continuous_training_pairs_by_source",
    "continuous_boundary_sd": 1.0,
    "global_parent_role_cap": 576,
    "global_schedule": "all five frozen V23.2 levels; L1/L2 retain 0.4 boundary",
    "near_rule": "standardized_logit_distance <= 1.0",
    "record_role_degree_cap": 96,
    "shortage_policy": "fill from available side",
    "target_near_fraction_per_query": 0.5,
    "validation_selection": "unchanged Morgan ranking pools"
  },
  "selection": "user-requested temperature0.5 with consistent empirical binary targets",
  "temperature": 0.5,
  "threshold_sd": 1.0
}