Bruxism an Issue Between the Myths and Facts
Bibliographic record
Abstract
Is our goal in this paper to discuss the current concepts about bruxism, a topic that has been a matter of discussion on the dental field for many years. Recent International efforts have been made to challenge bruxism old definitions; this has derivate to a consensus and an actual new concept that defines bruxism as a behavior instead of a disorder. As a behavior, it is explained in this review how it can have negative health consequences, can be innocuous and how new research support that bruxism can even be a protective factor. Different etiological factors are reviewed in this paper as well the influence of external and internal mechanism related to medications, emotional stress, systemic factors, and potential pharmacological pathways. Moreover, it is briefly summarized the role of oral appliances on sleep bruxism. Finally, clinical considerations and recommendation for the dental professional regarding sings that should be notice during the exam are part of this overview.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.020 |
| Scholarly communication | 0.006 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.019 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".