{
  "assertions": 6,
  "experiment": {
    "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": 0,
    "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
  },
  "status": "passed"
}