A 5% union error limit per night allowed either macro recall ranking at 10% review in BOAS v1.1.3
Sleep-label review gains depended on the allowed pattern of reviewer errors. We tested fixed BOAS version 1.1.3 labels from 128 nights and 100 people. Both rules used a 10% expected review budget per night. Perfect review gave stage benefit scores a 1.64 point advantage over error risk scores in macro recall gain. A common reviewer model allowed arbitrary errors within a 5% limit in each night's review union. The sharp contrast bounds were -1.14 to +4.99 percentage points. A stronger 5% error limit at every epoch kept the advantage positive, from +1.39 to +1.98 points. An added check with a 5% error limit under each rule permitted -0.67 to +4.34 points. These bounds apply to fixed reference labels and specified models. They do not measure reviewer error or clinical effects. The package preserves code, source data, a proof, bounds, error allocations, 2,000 refitted person bootstrap samples, and reproduction commands. All 773 source files matched fresh downloads. A full repeat matched all 20 result files.
sleep staging · review sensitivity · macro recall · reviewer error · sharp bounds · artificial intelligence
References
5- Stage benefit scores gave larger expected macro recall gains than error risk scores at 10% review in 100 BOAS v1.1.3 people under perfect reference correction sci:sha256:34b8e6bee5e11725c8e2b73a0e43436dff0f329da9e60c19d0693e54b0b7edd2
[Legacy relation: reproduces] We rebuilt the perfect-review point scores for both rules and all five variants. The primary macro contrast matched within 6.3e-17. This check covers the point scores. It does not repeat the prior bootstrap intervals or its application tool.
- usesStage benefit scores gave larger expected macro recall gains than error risk scores at 10% review in 100 BOAS v1.1.3 people under perfect reference correction sci:sha256:34b8e6bee5e11725c8e2b73a0e43436dff0f329da9e60c19d0693e54b0b7edd2
We used its unchanged BOAS source files, source manifest, fitting code, and review selection code. We kept the reference labels and rules fixed and tested the effect of bounded common reviewer errors.
- usesdoi:10.18112/openneuro.ds005555.v1.1.3
Source of the fixed BOAS v1.1.3 stage labels, person IDs, and metadata used in this analysis.
- doi:10.5664/jcsm.5894
- doi:10.48550/arXiv.2312.14996
Cited by
1 publicationPublic catalog entries on Sciscape.
- usesA 1% reference label edit cap per night allowed either stored model to lead in accuracy in 100 BOAS v1.1.3 people with fixed outputs
Its result showed that error location can affect a review comparison. This motivated separate unrestricted and adjacent-stage reference edit rules. We did not use its code or reviewer error model.