O gênero e a idade influenciam as dimensões do palato duro? Revisão sistemática da literatura
Bibliographic record
Abstract
PURPOSE: Analyze the influence of gender and age on hard palate dimensions and verify the reference parameters available in the literature. RESEARCH STRATEGIES: Two reviewers independently performed a search at the Cochrane Library, PubMed-Medline and Web of Knowledge databases using descriptors according to the syntax rules of each database. SELECTION CRITERIA: Observational or experimental human studies evaluating the dimensions of the hard palate or maxillary dental arch, with at least one transverse, vertical or sagittal plane measurement, in normal occlusions or class I malocclusions, and comparisons of the dimensions between genders and/or ages. DATA ANALYSIS: Descriptive analysis with the following subdivisions: design, sample, evaluation instruments, measurements in millimeters, and statistical analysis. Quality of the included studies was verified by the Newcastle - Ottawa Quality scale. RESULTS: Eighteen studies were selected and 11 presented results for hard palate or maxillary dental arch dimensions according to gender, six in age and gender and one in age only. CONCLUSION: The dimensions were larger in males and progressive increase in the measurements was observed from birth to the permanent dentition period.
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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 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.005 |
| Bibliometrics | 0.016 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".