Mandibular growth comparisons of Class I and Class II division 1 skeletofacial patterns
Bibliographic record
Abstract
OBJECTIVE: To determine class and sex differences in mandibular growth and modeling. MATERIALS AND METHODS: A mixed-longitudinal sample of 130 untreated French-Canadian adolescents, 77 (45 boys and 32 girls) with Class I (normal or abnormal) occlusion and 53 (26 boys and 27 girls) with Class II division 1 malocclusion, was used. Based on eight landmarks, eight traditional measurements were used to compare the anteroposterior position of the maxilla and mandible, relationship between the jaws, and mandibular size. Mandibular superimpositions were used to compare the horizontal and vertical changes of condylion, gonion, and menton. RESULTS: While there were no differences in maxillary position based on the SNA angle, Class IIs had more retrognathic mandibles than did Class Is. Total mandibular length was greater in Class Is than in Class IIs at 15 years of age. Superior and total growth and modeling changes at condylion and gonion, respectively, were greater for Class Is than Class IIs. Boys were more prognathic than girls; they had larger mandibles and exhibited greater size increases and growth changes than girls did. CONCLUSIONS: There are both class and sex differences in mandibular growth and modeling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".