Comparison of airway dimensions in skeletal Class I malocclusion subjects with different vertical facial patterns
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to compare upper airway widths among skeletal Class I malocclusion subjects with different vertical facial patterns. METHODS: The sample included a total of 99 lateral cephalograms of post pubertal individuals (18.19 ± 1.76 years old). The vertical facial pattern was determined by the Vert index. The McNamara method was used to quantify upper airway widths. ANOVA test and Student's t test for independent groups were used, when normal distribution was not supported Kruskal-Wallis test and U-Mann-Whitney test were used. A multiple linear regression analysis was also performed. RESULTS: Statistically significant differences in several nasopharyngeal widths were found among the distinct vertical facial patterns. Subjects with brachyfacial pattern presented larger nasopharyngeal widths than subjects with mesofacial (p= 0.030) or dolichofacial (p= 0.034) patterns. The larger the Vert value, the larger the nasopharyngeal widths (R2= 26.2%, p< 0.001). At the level of oropharynx no statistically significant differences were found. CONCLUSION: It was concluded that nasopharyngeal linear anteroposterior widths in Class I malocclusion brachyfacial are larger than in mesofacial and dolichofacial individuals. The Vert index only explained 25% of the total variability. No correlation was found for the oropharyngeal widths.
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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 | 0.001 | 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) | 0.003 | 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".