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Open_Ultra_SAST/benchmarks/experiments/exp-002-retrieval-ensemble/result.json
T
Marius CiepluchandClaude Fable 5.1 48510fd5c2 bench(learn): exp-002 result -- retrieval ensemble vs temperature sampling
Reject B. 160 paired units (injection 119, access_control 41; 56 repositories),
both arms, two replicates each, no early stop. Canary agreement A 0.875 -> B
0.906 (CI [-0.03, +0.10], spans; B meets 0.90). Within-pair AUC A 0.815 -> B
0.741 (CI [-0.13, -0.02], against B). AUC -0.02 (against), ADVISORY recall
-0.06 and precision +0.01 (span), usd per candidate A $0.0021 -> B $0.0051
(against). Priced usage A $0.68 / B $1.63; balance $16.72 -> $16.04 at the
run's end (lags). Counts only; task 7.4 marked done.

Co-Authored-By: Claude Fable 5.1 <[email protected]>
Claude-Session: https://claude.ai/code/session_01EmM1j46qgKMh3zqD1QMwEo
2026-10-02 19:05:34 +02:00

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5.6 KiB
JSON

{
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},
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}
},
"code_commit": "780caaa558f2cc091fd6b0fd5c618c3b488030c2",
"decision": "reject",
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"hypothesis": "Drawing the k = 5 samples from five disjoint retrieved example sets at temperature 0 (a retrieval ensemble) makes the decision more repeatable than five temperature samples over one example set, without hurting the ranking within a candidate pair, at no higher cost per candidate.\n",
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