{
  "absolute_gain_percentage_points": 16.667,
  "baseline": {
    "accuracy": 0.833333,
    "correct": 40,
    "decisions": 48,
    "per_context": {
      "deployment_failure": {
        "accuracy": 0.75,
        "correct": 12,
        "decisions": 16
      },
      "disk_pressure": {
        "accuracy": 0.75,
        "correct": 12,
        "decisions": 16
      },
      "network_timeout": {
        "accuracy": 1.0,
        "correct": 16,
        "decisions": 16
      }
    }
  },
  "candidate": {
    "accuracy": 1.0,
    "correct": 48,
    "decisions": 48,
    "per_context": {
      "deployment_failure": {
        "accuracy": 1.0,
        "correct": 16,
        "decisions": 16
      },
      "disk_pressure": {
        "accuracy": 1.0,
        "correct": 16,
        "decisions": 16
      },
      "network_timeout": {
        "accuracy": 1.0,
        "correct": 16,
        "decisions": 16
      }
    }
  },
  "candidate_accepted_by_gate": true,
  "claim": "On this deterministic synthetic workflow benchmark only, the context-aware procedural graph scored 100.0% versus 83.3% for the context-agnostic baseline (16.7 percentage points). The pilot also rejected unsupported success claims and abstained on an unseen context. This validates the pilot implementation's control behavior only; it does not establish improved real-world LLM-agent performance, general intelligence, or a new scientific discovery.",
  "completion_gate_tests": {
    "empty_gates_rejected": true,
    "failed_gate_rejected": true,
    "missing_evidence_reference_rejected": true,
    "passed_evidence_linked_gate_accepted": true
  },
  "cycle": 99,
  "dataset": {
    "actions": 13,
    "contexts": [
      "deployment_failure",
      "disk_pressure",
      "network_timeout"
    ],
    "external_calls": 0,
    "held_out_records": 12,
    "model_generated_code_executed": false,
    "train_records": 30
  },
  "literature_lookup_requested": false,
  "method": "Deterministic synthetic workflows; context-agnostic baseline versus context-aware transition graph trained only on training traces; failed transitions penalized; held-out decisions checked against a fixed evaluator specification.",
  "model_weights_updated": false,
  "no_per_context_regression": true,
  "novelty_status": "not a novelty claim; engineering pilot inspired by prior published work",
  "production_graph_updated": false,
  "status": "ok",
  "task": "procedural_graph_and_verifiable_completion_pilot",
  "unseen_context_abstention": {
    "passed": true,
    "prediction": null,
    "reason": "no_context_specific_evidence"
  },
  "validation_passed": true
}