Predictors of temporomandibular disorders : clinical variables and patient characteristics
Bibliographic record
Abstract
This case control study was designed to investigate the contributing factors for the occurrence of temporomandibular disorder (TMD) and its subgroups: myofascial pain (MFP) and disc displacement (DD). 178 patients with TMD were selected from the dental clinics of the Jewish General and Montreal General Hospitals, Montreal, Canada, and 100 concurrent controls selected only at the first clinic, participated in this study. The association with TMD, MFP and DD was evaluated for bruxism, trauma, psychological factors, and sociodemographic status using a logistic regression. Migraine, depression, and clenching were associated with the occurrence of TMD. Among the MFP patients, clenching, clenching-grinding, anxiety, female, depression, and somatization were associated with disease occurrence. In addition, adjusted analysis among the DD patients showed an association with clenching-grinding, orthodontic treatment, and anxiety. Our results identify possible risk factors that are associated with TMD, MFP, and DD occurrence. Further research needs to be conducted to look at these associations in depth.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".