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Nocturnal sleep architecture is altered by sleep bruxism

2017· article· en· W2609893109 on OpenAlexaff
Marcelo Palinkas, Marisa Semprini, João Espir Filho, Graziela De Luca Canto, Isabela Hallak Regalo, César Bataglion, Laíse Angélica Mendes Rodrigues, Selma Siéssere, Simone Cecílio Hallak Regalo

Bibliographic record

VenueArchives of Oral Biology · 2017
Typearticle
Languageen
FieldHealth Professions
TopicTemporomandibular Joint Disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNon-rapid eye movement sleepSleep (system call)PolysomnographySleep BruxismSlow-wave sleepSleep StagesMedicineK-complexSleep onset latencyAudiologyAnesthesiaPsychologySleep disorderEye movementInsomniaElectroencephalographyPsychiatryElectromyographyOphthalmologyApnea

Abstract

fetched live from OpenAlex

OBJECTIVE: Sleep is a complex behaviour phenomenon essential for physical and mental health and for the body to restore itself. It can be affected by structural alterations caused by sleep bruxism. The aim of this study was to verify the effects of sleep bruxism on the sleep architecture parameters proposed by the American Academy of Sleep Medicine. DESIGN: The sample comprised 90 individuals, between the ages of 18 and 45 years, divided into two groups: with sleep bruxism (n=45) and without sleep bruxism (n=45). The individuals were paired by age, gender and body mass index: a polysomnography was performed at night. RESULTS: Statistically significant differences were found between (P≤0.05) individuals with sleep bruxism and individuals without sleep bruxism during total sleep time (P=0.00), non-rapid eye movement (NREM) total sleep time (P=0.03), NREM sleep time stage 3 (P=0.03), NREM sleep latency (P=0.05), sleep efficiency (P=0.05), and index of microarousals (P=0.04). CONCLUSIONS: Sleep bruxism impairs the architecture of nocturnal sleep, interfering with total sleep time, NREM sleep latency, and sleep efficiency.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.037
GPT teacher head0.396
Teacher spread0.359 · 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".

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Citations34
Published2017
Admission routes1
Has abstractno

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