{
  "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_2c239daa:coef.cdl",
  "attempt": 1,
  "epoch": 1,
  "gold": {
    "effect": 0.003,
    "effect_as_stored": "0.003",
    "is_significant": 0,
    "source_id": "causcibench_real.gold.q017",
    "std_error": 0.017,
    "std_error_as_stored": "0.017"
  },
  "label": {
    "family": "did",
    "method": "did",
    "rule": "OLS with unit and time fixed effects; the regressor varies within unit",
    "tool_id": "infer.ols"
  },
  "native_id": 17,
  "precision_limited": true,
  "record": {
    "dataset_path": "data/csv_files/realdata/cheng_does_strengthening.csv",
    "effect": 0.003,
    "method": "did",
    "name": "Does strengthening self-defense law deter crime or escalate violence?",
    "query": "How do castle doctrine laws affect (log) larceny rates across states while accounting for population size across the states?",
    "result": {
      "final_result": {
        "causal_effect": 0.007453541783759591,
        "covariates": [
          "sid",
          "year"
        ],
        "method": "did",
        "outcome_variable": "l_larceny",
        "standard_deviation": 0.01084077138040986,
        "treatment_variable": "cdl"
      },
      "retries": null
    }
  },
  "scores": {
    "control_overlap": null,
    "effect_correct": 0,
    "method_correct": 1,
    "outcome_match": 1,
    "relative_error_pct": 100,
    "treatment_match": null
  },
  "status": "failed",
  "task_id": "causcibench_real.q017"
}