Demirjian Stage Tooth Formation Results from a Large Group of Children
Bibliographic record
Abstract
The aim of this study is to present further data on the timing and variation of individual permanent mandibular teeth using Demirjian stages from a large collaboration. Seven mandibular permanent teeth were assessed from dental radiographs of healthy dental patients from Australia, Belgium, Canada, England, Finland, France, South Korea and Sweden (cross-sectional study; n = 9,371, 4,710 males, 4,661 females; aged 2–18). Data are presented in three ways, namely by tooth stage for males, females, and pooled sex. Mean age at entry of each tooth formation stage (maturity data) was calculated using logistic regression and modified for age prediction. The 51% confidence interval for age within stage of individual tooth stages was calculated for use in forensic age estimation where the burden of proof is on the balance of probabilities. Average age, standard deviation, standard error, 3rd and 97th percentile within tooth stage was calculated from a uniform age sample (171 for each year of age from 3 to 16, n = 2,394). Modified maturity data and average age within stage from the uniform age distribution are two new methods of age estimation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.032 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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; both teacher heads agree on what is shown here.
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".