Efficiency of molar distalization associated with second and third molar eruption stage
Bibliographic record
Abstract
OBJECTIVE: To evaluate the efficiency of molar distalization associated with the second and third molar eruption stage. MATERIALS AND METHODS: A systematic computerized database search was conducted using several databases. Adaptations of the terms molar distalization and distalizing appliances were used. The reference lists of all the selected articles were also searched for any potential articles that might have been missed in the electronic search. The data provided in the selected publications were grouped and analyzed in terms of molar distalization with respect to various eruption stages of maxillary second and third molars. RESULTS: Out of the 13 initially identified articles only four fulfilled the final selection criteria. Three of the four studies showed no statistical significance in linear molar distalization based on the eruptive stage of the second and/or third molars, while one study found that the amount of distal movement of the first molars was significantly greater in the group with unerupted second molars. Only one study found that the amount of molar tipping that occurred as a result of distalization was related to the eruption stage of the maxillary molars. Similarly, three of the four studies found that molar distalization time was not significantly affected by eruption of the second or third molars. CONCLUSION: The effect of maxillary second and third molar eruption stage on molar distalization-both linear and angular distalization-appears to be minimal. This conclusion is only based on low-level of evidence clinical trials. The large variability in the outcomes should be considered clinically.
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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 | 0.016 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".