{
  "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_ec882079:coef.postxapple",
  "attempt": 1,
  "epoch": 1,
  "gold": {
    "effect": 0.133,
    "effect_as_stored": "0.133",
    "is_significant": 1,
    "source_id": "causcibench_real.gold.q106",
    "std_error": 0.022,
    "std_error_as_stored": "0.022"
  },
  "label": {
    "family": "did",
    "method": "did",
    "rule": "OLS with unit and time fixed effects; the regressor varies within unit",
    "tool_id": "infer.ols"
  },
  "native_id": 106,
  "precision_limited": false,
  "record": {
    "dataset_path": "data/csv_files/realdata/enache_demand_for.csv",
    "effect": 0.133,
    "method": "did",
    "name": "Demand for in-app purchases in mobile apps—a difference-in-difference approach",
    "query": "Does the number of users who purchase premium change after the price of premium is altered?",
    "result": {
      "final_result": {
        "causal_effect": 0.13358400959555405,
        "covariates": [
          "year",
          "month",
          "game",
          "country",
          "apple",
          "post"
        ],
        "method": "did",
        "outcome_variable": "norm_purch_users",
        "standard_deviation": 0.022339696786359893,
        "treatment_variable": "postxapple"
      },
      "retries": null
    }
  },
  "scores": {
    "control_overlap": 1.0,
    "effect_correct": 1,
    "method_correct": 1,
    "outcome_match": 1,
    "relative_error_pct": 0.43910495906319313,
    "treatment_match": null
  },
  "status": "passed",
  "task_id": "causcibench_real.q106"
}