Modified Demirjian’s method for dental age estimation in Kosovar children and adolescents
Bibliographic record
Abstract
AIM: The aim was to provide normative data on dental age estimation in the Kosovar population, to evaluate the relationship between customized maturity scores and the original Demirjian method, and to assess the accuracy of these scores in a sample of Kosovar children and adolescents. MATERIALS AND METHODS: The study population consisted of 1106 digital panoramic radiographs randomly selected from 6- to 16-year-old patients treated at the University Dentistry Clinical Center of Kosovo. Only those images that were diagnostically acceptable, thus showing at least the left mandibular teeth, were included in the study to assess the developmental stage accurately. RESULTS: Dental age estimates derived from the Kosovar normative tables were comparable to those based on maturity scores for the French-Canadian population. In girls aged 7.5-13 years and boys aged 7.5-12 years, dental maturity correlated strongly. However, the French-Canadian model overestimated age significantly compared to the Kosovar sample, where dental maturity started at about 6 years and peaked at 7 years. The Spearman's rho of the relationship between dental ages determined by Demirjian's method and maturity scores obtained from both populations was 0.997 for girls and 0.988 for boys. In conclusion, the present study demonstrates the need for population-specific adaptations of the Demirjian method and proves that modification of the method provides more reliable results when compared to the Kosovar population. The results indicate the possibility of further refinement of the Demirjian method for specific populations in order to improve the applicability and precision of the most commonly used method for age estimation.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".