{
  "about": "CauSciBench native output: 'record' has the shape their evaluation/extract.py reads (a run's records in one list rescore with their evaluation/run_evaluation.py); the method is the tool-family label of the answer call (tool-family accuracy from tool calls, not a method the model named); 'scores' are the per-item terms of evaluation/metrics.py.",
  "answer_ref": "call_3de0dbb9:coef.trustprime",
  "attempt": 1,
  "epoch": 1,
  "gold": {
    "effect": 20.372,
    "effect_as_stored": "20.372",
    "is_significant": 1,
    "source_id": "causcibench_real.gold.q036",
    "std_error": 0.812,
    "std_error_as_stored": "0.812"
  },
  "label": {
    "family": "ols",
    "method": "ols",
    "rule": "regression",
    "tool_id": "infer.ols"
  },
  "native_id": 36,
  "precision_limited": false,
  "record": {
    "dataset_path": "data/csv_files/realdata/liu_public_trust1.csv",
    "effect": 20.372,
    "method": "ols",
    "name": "Public trust and collaborative governance: An instrumental variable approach",
    "query": "Does change to a different government integrity information affect trust in government?",
    "result": {
      "final_result": {
        "causal_effect": 20.371720848235373,
        "covariates": [],
        "method": "ols",
        "outcome_variable": "trust",
        "standard_deviation": 0.8241968868803874,
        "treatment_variable": "trustprime"
      },
      "retries": null
    }
  },
  "scores": {
    "control_overlap": 1.0,
    "effect_correct": 1,
    "method_correct": 1,
    "outcome_match": 1,
    "relative_error_pct": 0.00137027176824348,
    "treatment_match": 1
  },
  "status": "passed",
  "task_id": "causcibench_real.q036"
}