Impact of sleep bruxism on masseter and temporalis muscles and bite force
Bibliographic record
Abstract
OBJECTIVES: This study aimed to analyze the impact of sleep bruxism (SB) on electromyography (EMG) activity and the thickness of the masseter and temporal and maximal molar bite force. METHOD: Ninety individuals, aged between 18 and 45 years, were selected and divided into two groups: Group I (case group, 45 individuals with SB) and Group II (control group, 45 individuals without SB). A diagnosis of SB was made from polysomnography. RESULTS: The data obtained from EMG and the muscle thickness and the maximal molar bite force were tabulated (SPSS 21.0), normalized, and subjected to statistical analysis (p ≤ 0.05). Comparisons between the groups showed significant differences regarding the habitual chewing of hard food for the left temporalis muscle (p = 0.04) and the chewing of soft food for the right masseter muscle (p = 0.04), but no significant differences for the measurements of muscle thickness and maximal molar bite force. DISCUSSION: The present data suggest that SB negatively altered the masticatory muscles' functions. Based on the results of this research, it can be concluded that individuals with SB showed decreased EMG activity in the masticatory muscles.
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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) | 0.002 | 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".