Exploring the potential of rapid maxillary expansion and masticatory muscle activity in unilateral posterior crossbite
Bibliographic record
Abstract
Background: This systematic review and meta-analysis aimed to evaluate if rapid maxillary expansion improves the activity of the masticatory muscles (masseter and temporal) in patients with unilateral posterior crossbite. Material and Methods: Searches were performed in PubMed/MEDLINE, Scopus, Web of Science, Embase, Cochrane Library, and grey literature. A manual search of orthodontic journals was also performed. Randomized clinical trials or longitudinal prospective studies were eligibles. Meta-analyses were conducted using R software with the "Meta" package, applying mean differences with a 95% confidence interval. Risk of bias was assessed using the Newcastle-Ottawa scale, and evidence certainty was evaluated using GRADE. Results: Nine articles were included. Qualitative analysis showed that RME treatment in patients with unilateral posterior crossbite showed a positive correlation with improvement in masseter and temporalis muscle activity. Meta-analyses indicated a significant difference for all models of muscle activity after treatment with rapid maxillary expansion, except for the temporal muscle in the force exerted on the maximum voluntary clenching on cotton rolls. The studies showed low bias risk, and the evidence certainty for each analysis was generally low to very low. Conclusions: Rapid maxillary expansion, masticatory muscles, unilateral posterior crossbite, systematic review, meta-analysis.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.017 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".