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Record W2142857014 · doi:10.1080/01612840500503047

SLEEPINESS AND RELATIONSHIPS IN OBSTRUCTIVE SLEEP APNEA

2006· article· en· W2142857014 on OpenAlexaff
Judith L. Reishtein, Allan I Pack, Greg Maislin, David F. Dinges, Thomas J. Bloxham, Charles F. George, Harly Greenberg, Gihan A. Kader, Mark W. Mahowald, Joel Younger, Terri E. Weaver

Bibliographic record

VenueIssues in Mental Health Nursing · 2006
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsWestern University
Fundersnot available
KeywordsEmbarrassmentObstructive sleep apneaIntrapersonal communicationMoodPsychologyClinical psychologyInterpersonal communicationAngerInterpersonal relationshipSleep (system call)MedicineDevelopmental psychologySocial psychologyInternal medicine

Abstract

fetched live from OpenAlex

This is a qualitative analysis of data from a multisite study of 156 participants with Obstructive Sleep Apnea (OSA). Participants completed a battery of tests, including the Functional Outcomes of Sleep Questionnaire (FOSQ) that contains an item assessing the impact of OSA on relationships. Approximately one third of participants wrote comments; they were predominately male, mean age 44.7, with severe OSA. Interpersonal themes expressed included work and marital problems and social life restriction. Intrapersonal themes included embarrassment and poor mood. This report adds specific details to previous reports of impaired relationships in OSA, and stresses the importance of assessing this critical area.

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)0.003
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.029
GPT teacher head0.373
Teacher spread0.344 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations47
Published2006
Admission routes1
Has abstractyes

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