Mandibular skeletal growth and modelling between 10 and 15 years of age
Bibliographic record
Abstract
This study pertains to a random sample of untreated French-Canadian adolescents (79 females and 107 males) evaluated at 10 and again at 15 years of age. Superimpositions on natural reference structures were performed to describe condylar growth and modelling of 11 mandibular landmarks. Superimpositions on natural cranial/cranial base reference structures were performed to describe mandibular displacement and true rotation. The results showed significant superior and posterior growth/modelling of the condyle and ramus. Males underwent significantly (P < 0.01) greater condylar growth and ramus modelling than females. With the exception of point B, which showed significant superior drift, modelling changes for the corpus landmarks were small and variable. The mandible rotated forward 2-3.3 degrees and was displaced 9.6-12.7 mm inferiorly and 1.9-2.7 mm anteriorly. Individual differences in ramus growth and modelling, both amount and direction, can be explained by mandibular rotation and displacements. Multivariate assessments revealed that superior condylar growth and ramus modelling were most closely associated with forward rotation and inferior mandibular displacement. Posterior growth and modelling were most closely correlated with anterior mandibular displacement and forward rotation. Modelling of the lower anterior border was independent of rotation and displacement.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".