Identification of a Sleep Bruxism Subgroup with a Higher Risk of Pain
Bibliographic record
Abstract
Sleep bruxism research diagnostic criteria (SB-RDC) have been applied since 1996. This study was performed to validate these criteria and to challenge the hypothesis that pain is associated with lower frequencies of orofacial activities. Polygraphic recordings were made of 100 individuals presenting with a clinical diagnosis of sleep bruxism and 43 control individuals. TwoStep Cluster analyses (SPSS) were performed with sleep bruxism variables to reveal groupings among sleep bruxers and control individuals. Participants completed questionnaires during screening, diagnosis, and recording sessions. Cluster analysis identified three subgroups of sleep bruxers. Interestingly, 45 of the 46 sleep bruxers with values below SB-RDC were classified in the low-frequency cluster. These individuals were more likely to complain of pain and fatigue of masticatory muscles than were the higher-frequency sleep bruxers (odds ratios > 3.9, p < 0.01). Sleep bruxers were distributed among three heterogeneous groups. Sleep bruxers with low frequencies of orofacial activities were more at risk of reporting pain.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".