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Record W1976882776 · doi:10.1177/00220345010800020801

Rhythmic Masticatory Muscle Activity during Sleep in Humans

2001· article· en· W1976882776 on OpenAlexafffund
Gilles Lavigne, Pierre Rompré, Gaétan Poirier, H. Huard, Takafumi Kato, Jacques Montplaisir

Bibliographic record

VenueJournal of Dental Research · 2001
Typearticle
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsUniversité de MontréalHôpital du Sacré-Cœur de Montréal
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsSleep BruxismElectromyographyMasticatory forceSleep (system call)MedicinePolysomnographyRhythmMasseter musclePhysical therapyAudiologyDentistryPhysical medicine and rehabilitationAnesthesiaInternal medicine

Abstract

fetched live from OpenAlex

Rhythmic Masticatory Muscle Activity (RMMA) is frequently observed during sleep in normal subjects and sleep bruxers. We hypothesized that some normal subjects exhibit RMMA at a lower frequency than sleep bruxers. Polysomnographic data from 82 normal subjects were compared with data from 33 sleep bruxers. RMMA episodes were defined as three or more consecutive bursts of masseter EMG activity, with or without tooth-grinding. Such episodes were observed in nearly 60% of normal subjects. A lower frequency of episodes was noted in normal subjects than in bruxers. Sleep organization was similar between groups. Bruxers had twice as many masseter muscle bursts per episode and episodes of higher amplitude compared with controls with RMMA. The high prevalence of RMMA observed in normal subjects suggests that this activity is related to certain sleep-related physiological functions, including autonomic activation.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.064
GPT teacher head0.401
Teacher spread0.337 · 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

Citations311
Published2001
Admission routes2
Has abstractyes

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