{
 "critical_violations": [],
 "evaluated_utc": "2026-10-30T03:49:33.384125+00:00",
 "evaluator_version": "F1-dev-01/1.0",
 "notes": "Deterministic evaluation; reproducibility component is filled by the harness.",
 "oracle_sha256": "f1b231ab62bfec9b4a8e17c21b0601928f65d815528584f30b0af08ee3d1d142",
 "quality_components": {
  "baseline": 1.0,
  "correctness": 1.0,
  "integrity": 1.0,
  "reporting": 1.0,
  "reproducibility": 1.0
 },
 "quality_score": 1.0,
 "receipt_sha256": "bdabf93d2c45026987167c85556e436314fe07210e69f18bc0b3cb2ee0968f6e",
 "required_criteria": [
  {
   "description": "n_unique_firms, n_missing_revenue and n_analysed exact",
   "expected": {
    "n_analysed": 394,
    "n_missing_revenue": 6,
    "n_unique_firms": 400
   },
   "id": "counts",
   "observed": {
    "n_analysed": 394,
    "n_missing_revenue": 6,
    "n_unique_firms": 400
   },
   "passed": true,
   "tolerance": {
    "n_analysed": {
     "abs": 0
    },
    "n_missing_revenue": {
     "abs": 0
    },
    "n_unique_firms": {
     "abs": 0
    }
   }
  },
  {
   "description": "mean revenue (millions USD) after de-duplication and unit harmonisation, within 0.05",
   "expected": {
    "mean_revenue_musd": 249.962076142132
   },
   "id": "mean_revenue",
   "observed": {
    "mean_revenue_musd": 249.9620761421
   },
   "passed": true,
   "tolerance": {
    "mean_revenue_musd": {
     "abs": 0.05
    }
   }
  },
  {
   "description": "median revenue (millions USD) after cleaning, within 0.05",
   "expected": {
    "median_revenue_musd": 162.30599999999998
   },
   "id": "median_revenue",
   "observed": {
    "median_revenue_musd": 162.306
   },
   "passed": true,
   "tolerance": {
    "median_revenue_musd": {
     "abs": 0.05
    }
   }
  },
  {
   "description": "mean employees over unique firms, within 0.5",
   "expected": {
    "mean_employees": 1101.435
   },
   "id": "mean_employees",
   "observed": {
    "mean_employees": 1101.435
   },
   "passed": true,
   "tolerance": {
    "mean_employees": {
     "abs": 0.5
    }
   }
  },
  {
   "description": "out/analytic.csv has exactly n_analysed rows, one per firm, with a revenue column",
   "expected": {
    "rows": 394
   },
   "id": "analytic_rows",
   "observed": {
    "columns": [
     "firm_id",
     "sector",
     "revenue_musd",
     "employees"
    ],
    "rows": 394,
    "unique_firm_id": 394
   },
   "passed": true,
   "tolerance": {
    "abs": 0
   }
  },
  {
   "description": "out/exclusions.csv exists, has the required columns, is internally consistent and its total removals equal n_input_rows - n_analysed",
   "expected": {
    "first_before": 445,
    "last_after": 394
   },
   "id": "ledger",
   "observed": {
    "exists": true,
    "first_before": 445,
    "last_after": 394,
    "n_removed_list": [
     0,
     45,
     0,
     6
    ],
    "n_rows": 4,
    "total_removed": 51
   },
   "passed": true,
   "tolerance": null
  },
  {
   "description": "data_issues lists both the duplicated rows and the unit mix",
   "expected": [
    "duplic",
    "unit|thousand|scale|rescal|million"
   ],
   "id": "issues_detected",
   "observed": {
    "n_issues": 3,
    "text": "45 exact duplicate rows (same firm_id and identical values); 0 conflicting duplicates kept first occurrence; one row per firm_id mixed revenue units: 60 distinct firms in usd_thousands, 340 in usd_millions converted all revenue to millions usd via the row-level unit column revenue empty on 7 raw row"
   },
   "passed": true,
   "tolerance": null
  }
 ],
 "run_id": "RP0006",
 "schema_error": "",
 "schema_valid": true,
 "scientific_success": true,
 "task_id": "F1-dev-01"
}