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Record W1513041136 · doi:10.1002/0470018860.s00441

Sleep Reduction, Cognitive Effects of

2005· other· en· W1513041136 on OpenAlexaff
John P. J. Pinel, Steven J. Barnes

Bibliographic record

VenueEncyclopedia of Cognitive Science · 2005
Typeother
Languageen
FieldPsychology
TopicSleep and Work-Related Fatigue
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsVigilance (psychology)Sleep lossSleep (system call)MoodAudiologyCognitionPsychologyEffects of sleep deprivation on cognitive performanceSlow-wave sleepSleep deprivationMedicineClinical psychologyPsychiatryCognitive psychologyElectroencephalographyComputer science

Abstract

fetched live from OpenAlex

Abstract Even minor sleep loss (e.g., 3 or 4 hours for one night) increases sleepiness, disturbs mood, and reduces vigilance. More complex cognitive and motor disturbances have been reported after sleep loss, but they have been proven to be less sensitive. Remarkably, the few studies of individuals who have adopted long programs of reduced sleep (e.g., 5.5 hours per night) suggest that their sleep gradually becomes more efficient, and their initial deficits diminish.

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)0.000
metaresearch head score (Gemma)0.000
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: Other · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0160.001

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 head0.007
GPT teacher head0.294
Teacher spread0.286 · 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
GenreOther

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
Published2005
Admission routes1
Has abstractyes

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