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Record W6931924143 · doi:10.5683/sp3/8zeawt

SS1 Sleep Annotations

2021· dataset· en· W6931924143 on OpenAlexaboutno aff

Bibliographic record

VenueBorealis · 2021
Typedataset
Languageen
FieldMathematics
TopicMathematical Approximation and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsSleep (system call)CohortSleep StagesCohort studySleep patternsEye movement

Abstract

fetched live from OpenAlex

The SS1 subset of the Montreal Archive of Sleep Studies (MASS) cohort includes : 53 subjects (age 63±5.3 years, age range: 55-76 years) 34 males (age 63.5±5.6 years, age range: 55-76 years) 19 females (age 63.7±4.9 years, age range: 56-72 years) The SS1 subset includes sleep annotations and sleep stages. Annotations: Expert annotations: Apnea/hypopnea Micro arousal Automatic detection: Muscular artefacts Periodic limb movements of sleep (PLMS) Sleep stage scoring : Rules : AASM Page size (s) : 30

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.259
Threshold uncertainty score0.868

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.2590.105

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.057
GPT teacher head0.338
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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