{
  "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_6aa2cf12:coef.educ",
  "attempt": 1,
  "epoch": 1,
  "gold": {
    "effect": 0.132,
    "effect_as_stored": "0.132",
    "is_significant": 1,
    "source_id": "causcibench_real.gold.q009",
    "std_error": 0.049,
    "std_error_as_stored": "0.049"
  },
  "label": {
    "family": "iv",
    "method": "iv",
    "rule": "two-stage least squares",
    "tool_id": "infer.iv_2sls"
  },
  "native_id": 9,
  "precision_limited": false,
  "record": {
    "dataset_path": "data/csv_files/realdata/card_using_geographic.csv",
    "effect": 0.132,
    "method": "iv",
    "name": "Using geographic variation in college proximity to estimate the return to schooling",
    "query": "What is the effect of education on earnings?",
    "result": {
      "final_result": {
        "causal_effect": 0.13184969617215697,
        "covariates": [
          "exper",
          "black",
          "south",
          "smsa"
        ],
        "method": "iv",
        "outcome_variable": "lwage",
        "standard_deviation": 0.04883877859916181,
        "treatment_variable": "educ"
      },
      "retries": null
    }
  },
  "scores": {
    "control_overlap": 1.0,
    "effect_correct": 1,
    "method_correct": 1,
    "outcome_match": 1,
    "relative_error_pct": 0.1138665362447232,
    "treatment_match": 1
  },
  "status": "passed",
  "task_id": "causcibench_real.q009"
}