Create dataset_schema_.json

dataset_schema_.json

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+{
+  "version": "0.3",
+  "benchmark_name": "CASSES",
+  "description": "Clarus Adversarial State-Space Evaluation Standard v0.3",
+
+  "splits": [
+    "train",
+    "in_domain_test",
+    "boundary_trap",
+    "distribution_shift",
+    "counterfactual_intervention"
+  ],
+
+  "trap_types": [
+    "false_stability",
+    "boundary_masking",
+    "trajectory_aliasing",
+    "temporal_alias",
+    "intervention_decoy"
+  ],
+
+  "difficulty_levels": [
+    "easy",
+    "medium",
+    "hard"
+  ],
+
+  "pair_roles": [
+    "safe_pair",
+    "unstable_pair"
+  ],
+
+  "thresholds": {
+    "low_boundary_distance": 0.10,
+    "high_drift_gradient": 0.05
+  },
+
+  "required_prediction_fields": [
+    "scenario_id",
+    "prediction"
+  ],
+
+  "optional_prediction_fields": [
+    "intervention_effect_direction"
+  ],
+
+  "required_truth_fields": [
+    "scenario_id",
+    "split_type",
+    "pair_id",
+    "pair_role",
+    "difficulty_level",
+    "pressure_obs_t0",
+    "pressure_obs_t1",
+    "pressure_obs_t2",
+    "buffer_obs_t0",
+    "buffer_obs_t1",
+    "buffer_obs_t2",
+    "true_label",
+    "trap_type",
+    "trap_active",
+    "boundary_distance",
+    "drift_gradient",
+    "drift_acceleration",
+    "recovery_feasibility",
+    "regime_competition_ratio",
+    "intervention_action",
+    "intervention_magnitude",
+    "boundary_distance_before",
+    "boundary_distance_after",
+    "intervention_effect_direction"
+  ],
+
+  "metrics": {
+    "basic": [
+      "accuracy",
+      "precision",
+      "recall",
+      "f1",
+      "rows_evaluated"
+    ],
+    "split_metrics": [
+      "train_accuracy",
+      "in_domain_test_accuracy",
+      "boundary_trap_accuracy",
+      "distribution_shift_accuracy",
+      "counterfactual_intervention_accuracy"
+    ],
+    "trap_metrics": [
+      "trap_accuracy",
+      "false_stability_accuracy",
+      "boundary_masking_accuracy",
+      "trajectory_aliasing_accuracy",
+      "temporal_alias_accuracy",
+      "intervention_decoy_accuracy"
+    ],
+    "difficulty_metrics": [
+      "easy_accuracy",
+      "medium_accuracy",
+      "hard_accuracy"
+    ],
+    "geometry_metrics": [
+      "low_boundary_distance_miss_rate",
+      "high_drift_gradient_miss_rate"
+    ],
+    "counterfactual_metrics": [
+      "counterfactual_intervention_accuracy",
+      "intervention_effect_direction_accuracy"
+    ],
+    "pair_metrics": [
+      "trajectory_pair_discrimination_accuracy"
+    ],
+    "support_metrics": [
+      "train_support",
+      "in_domain_test_support",
+      "boundary_trap_support",
+      "distribution_shift_support",
+      "counterfactual_intervention_support",
+      "trap_support"
+    ],
+    "composite_metrics": [
+      "manifold_generalization_gap",
+      "casses_score"
+    ]
+  },
+
+  "composite_score": {
+    "name": "casses_score",
+    "weights": {
+      "in_domain_test_accuracy": 0.18,
+      "boundary_trap_accuracy": 0.20,
+      "distribution_shift_accuracy": 0.17,
+      "trap_accuracy": 0.15,
+      "counterfactual_intervention_accuracy": 0.15,
+      "trajectory_pair_discrimination_accuracy": 0.15
+    },
+    "renormalize_if_missing": true
+  },
+
+  "manifold_generalization_gap": {
+    "formula": "in_domain_test_accuracy - distribution_shift_accuracy"
+  },
+
+  "pair_discrimination_rule": {
+    "description": "For each pair_id, one row must have pair_role=safe_pair and one row must have pair_role=unstable_pair. A pair is correct only if the unstable row is predicted 1 and the safe row is predicted 0."
+  },
+
+  "counterfactual_rule": {
+    "description": "Rows in counterfactual_intervention evaluate whether the model correctly predicts the outcome label and, when provided, the intervention effect direction."
+  },
+
+  "validation_rules": {
+    "prediction_binary_values": [0, 1],
+    "truth_binary_values": {
+      "true_label": [0, 1],
+      "trap_active": [0, 1]
+    },
+    "intervention_effect_direction_values": [-1, 0, 1],
+    "require_exact_scenario_id_match": true,
+    "require_unique_scenario_id": true,
+    "allow_null_trap_type": true,
+    "allow_null_pair_id": true,
+    "allow_null_pair_role": true
+  },
+
+  "interpretation": {
+    "accuracy": "Overall classification correctness",
+    "trap_accuracy": "Performance on trap-active rows only",
+    "boundary_trap_accuracy": "Performance on boundary deception rows",
+    "distribution_shift_accuracy": "Performance when observable manifold shifts",
+    "counterfactual_intervention_accuracy": "Performance on intervention outcome rows",
+    "trajectory_pair_discrimination_accuracy": "Ability to distinguish paired safe vs unstable trajectories",
+    "low_boundary_distance_miss_rate": "Fraction of unstable near-boundary rows predicted stable",
+    "high_drift_gradient_miss_rate": "Fraction of unstable high-drift rows predicted stable",
+    "casses_score": "Composite state-space reasoning benchmark score"
+  },
+
+  "output_format": {
+    "type": "json",
+    "required_output_keys": [
+      "accuracy",
+      "precision",
+      "recall",
+      "f1",
+      "rows_evaluated",
+      "train_accuracy",
+      "in_domain_test_accuracy",
+      "boundary_trap_accuracy",
+      "distribution_shift_accuracy",
+      "trap_accuracy",
+      "false_stability_accuracy",
+      "boundary_masking_accuracy",
+      "trajectory_aliasing_accuracy",
+      "temporal_alias_accuracy",
+      "intervention_decoy_accuracy",
+      "easy_accuracy",
+      "medium_accuracy",
+      "hard_accuracy",
+      "manifold_generalization_gap",
+      "low_boundary_distance_miss_rate",
+      "high_drift_gradient_miss_rate",
+      "counterfactual_intervention_accuracy",
+      "intervention_effect_direction_accuracy",
+      "trajectory_pair_discrimination_accuracy",
+      "train_support",
+      "in_domain_test_support",
+      "boundary_trap_support",
+      "distribution_shift_support",
+      "counterfactual_intervention_support",
+      "trap_support",
+      "casses_score"
+    ]
+  }
+}