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"purpose": "The published report carries normalized scores for the published tasks only. This hash commits to the complete unredacted evaluation so it can be audited without being disclosed, and released once its test episodes retire.",
"artifacts": [
{
"name": "unredacted evaluation report, all tasks",
"contains": "raw net P&L, maximum drawdown, Sharpe and per-product P&L for every model task run and human strategy replay on the private test episodes, for the published tasks and the reserve alike, plus per-task human anchor values and team mapping",
"release_condition": "published when its test episodes are retired"
}
],
"how_to_audit": "Request the committed file under separate terms, hash it, compare, then recompute each score with sdk/quant_trading/scoring.py and SCORING.md."