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Record W2029089784 · doi:10.1139/y06-095

The public health and safety consequences of sleep disordersThis paper is one of a selection of papers published in this Special Issue, entitled Young Investigators' Forum.

2007· review· en· W2029089784 on OpenAlexaffvenue
Krista Sigurdson, Najib Ayas

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2007
Typereview
Languageen
FieldPsychology
TopicSleep and Work-Related Fatigue
Canadian institutionsUniversity of British Columbia Hospital
Fundersnot available
KeywordsMedicinePublic healthObstructive sleep apneaSleep deprivationSleep (system call)Sleep apneaIntensive care medicineDiseaseSleep medicineGerontologyPsychiatrySleep disorderFamily medicineNursingInsomniaPathology

Abstract

fetched live from OpenAlex

Sleep deprivation and medical disorders of sleep are common in today's society and have significant public health implications. In this article, we address 3 specific issues related to the public health and safety consequences of sleep disorders. First, we review data that has linked sleep restriction to a variety of adverse physiologic and long-term health outcomes including all-cause mortality, diabetes, and cardiovascular disease. Second, we will review recent data that has demonstrated that therapy for obstructive sleep apnea (the most common respiratory disorder of sleep) is an extremely efficient use of healthcare resources (in terms of dollars spent per quality adjusted life year gained), and compares favorably with other commonly funded medical therapies. Finally, we will review data that illustrate the potential adverse patient and occupational safety impacts of the extreme work schedules of housestaff (physicians in training).

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)0.003
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.002

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 head0.038
GPT teacher head0.333
Teacher spread0.296 · 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
GenreReview

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

Citations89
Published2007
Admission routes2
Has abstractyes

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