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{
"checks": [
{
"check": "validated tasks",
"value": 957,
"criterion": "= 957",
"passed": true
},
{
"check": "patch-size ratio",
"value": 5.277777777777778,
"criterion": "within 0.1 of reported 5.2x",
"passed": true
},
{
"check": "task-workload pairs",
"value": 253222.2,
"criterion": "> 250,000",
"passed": true
},
{
"check": "validation p threshold",
"value": 0.002,
"criterion": "< 0.01",
"passed": true
}
],
"scope": "Independent arithmetic audit of the reported dataset funnel and benchmark summary; agent inference was not rerun.",
"paper_id": "WArbqRUsAe",
"title": "FormulaCode: Evaluating Agentic Optimization on Large Codebases",
"seed": 1082026,
"executed_at": "2026-08-01T09:33:34.772522+00:00",
"all_checks_passed": true,
"environment": {
"python": "3.10.12",
"numpy": "1.24.4",
"scipy": "1.14.0",
"platform": "Linux-5.15.0-139-generic-x86_64-with-glibc2.35"
},
"reference_evidence": {
"space": "Srishti280992/repro-formulacode-evaluating-agentic-optimization-on-large-codebases",
"sha": "353c018b3843ae98dd37e06c841202cdf2f80ee3",
"relationship": "separately attributed public reference"
}
}