Mandibular movement during sleep bruxism associated with current tooth attrition
Bibliographic record
Abstract
PATIENT: Observation of attrition patterns suggests that mandibular movement in sleep bruxism (SB) may be associated with current tooth attrition. The aim of this study was to confirm this phenomenon by investigating mandibular movement and masseter muscle activity. The subject was a healthy 21-year-old Japanese male. We recorded biological signals including mandibular movement and masseter electromyograms (EMGs) with a polysomnograph. Based on the EMG using Okura's criteria, SB events were classified into clenching, grinding and mixed types according to mandibular movement criteria. The close-open mandibular movement cycles (CO-cycles) during grinding and mixed type events were selected based on mandibular movement trajectories. DISCUSSION: Fifty-eight CO-cycles were selected in seven grinding and three mixed types. We found that SB mandibular movements associated with current tooth attrition. Excessive lateral movements (ELM) beyond the canine edge-to-edge position were observed in the closing (10.3%) and opening (13.8%) phases of the CO-cycle. Total masseter muscle activity was significantly higher during voluntary grinding (VGR) than during CO-cycle including ELM (working side: P=0.036, balancing side: P=0.025). However, in the middle and late parts of the opening phase, working side masseter muscle activity was significantly higher during CO-cycle including ELM than during VGR (P=0.012). In the early part of the closing phase, balancing side masseter muscle activity was significantly higher during CO-cycle including ELM than during VGR (P=0.017). CONCLUSION: These findings suggest that excessive forceful grinding during ongoing SB events may have caused canine attrition in this patient.
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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 | 0.000 | 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".