Cephalometric Mandibular Dimensions in Growing Turkish Children: Trends of Change, Sex-Specific Differences, and Comparisons with Published Norms
Bibliographic record
Abstract
OBJECTIVE: The aims of this study were to investigate cephalometric mandibular dimensions in growing Anatolian Turkish children and to identify the periods of rapid growth for boys and girls. Furthermore, the secondary aim was to compare obtained values with published standards in the literature. METHODS: A total of 528 pretreatment lateral cephalometric radiographs, grouped according to age and sex, were analyzed. Effective mandibular length, ramus height, and corpus lengths were comparatively evaluated within age groups for boys and girls and between sexes for the same age group. Data acquired from this study were compared with American, Canadian, Chinese, and European norms. Growth curves for mandible were constructed for each sex group. RESULTS: Effective mandibular length was almost always significantly longer in boys, except for 9- and 12-year-age groups. Effective mandibular length in girls increased significantly between ages 8 and 10, 10 and 12, and 11 and 13 years, while in boys between ages 8 and 10, 9 and 11, and 13 and 15 years. Turkish girls had significantly shorter effective mandibular lengths than American girls at age 14. No significant difference was found between Turkish and Chinese girls and boys. Turkish girls and boys had significantly shorter corpus lengths from their Norwegian counterparts at age 12. CONCLUSION: Except for 9- and 12-year-age groups, effective mandibular length was almost always significantly longer in boys compared to the girls. It is suggested to use norm values from more recently conducted studies and which are representative of the studied population. Growth curves can be used to predict the approximate mandibular dimensions at a particular age.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".