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Record W91393298

The effect of glutamate-evoked masseter muscle pain on the human jaw-stretch reflex differs in men and women.

2003· article· en· W91393298 on OpenAlexaff
Brian E. Cairns, Kelun Wang, James W. Hu, Barry J. Sessle, Lars Arendt‐Nielsen, Peter Svensson

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldHealth Professions
TopicTemporomandibular Joint Disorders
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsJaw jerk reflexReflexMasseter muscleGlutamate receptorMedicineStretch reflexAnesthesiaAnatomyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

AIMS: To compare jaw-stretch reflex responses in male and female subjects and to determine whether injection of glutamate into the masseter muscle facilitates these responses in both sexes. METHODS: Jaw-stretch reflex responses were evoked with a muscle stretcher, and pain intensity was scored by 11 men and 13 women before and after the injection of glutamate (1.0 mol/L, 0.2 ml) into the masseter muscle. The subjects rated glutamate-evoked pain intensity on a visual analog scale. RESULTS: Baseline jaw-stretch reflex responses were larger and glutamate injections into the masseter muscle were significantly more painful in women than in men, however, glutamate significantly facilitated jaw-stretch reflex responses in men but not in women. CONCLUSION: These results suggest that there is a significant sex-related difference in human jaw-stretch reflex responses and their modulation by painful stimuli. Since one possible function of facilitated jaw-stretch reflex responses during jaw muscle pain may be to reduce jaw mobility and thus protect against further exacerbation of an existing injury, the finding of a sex-related difference in modulation of jaw-stretch reflex responses may prove to be important in clarifying why the prevalence of temporomandibular disorders is greater in women than in men.

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 score0.005
Threshold uncertainty score0.017

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)0.0050.001

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 head0.025
GPT teacher head0.311
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 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

Citations74
Published2003
Admission routes1
Has abstractyes

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