[Age estimation of children in south-western Hungary using the modified Demirjian method].
Bibliographic record
Abstract
The biological age of a child, in contrast to his or her chronological age, may be described in terms of skeletal or dental maturity, the development of secondary sex characters etc. These factors can be applied separately or together to assess the degree of physiological maturity of a growing child. The determination of this physiological age and its correlation to the chronological age is of importance within many fields, such as archaeology, forensic medicine, endocrinology, orthodontics etc. Dental maturity was studied on 203 panoramic radiographs, taken between 1985 and 1995, of healthy Hungarian children aged 2.9 to 17.5 years from the south-west Transdanubian part of Hungary. The revised method of Demirjian was used for determination of the maturity score of each individual. For each tooth a score (on a scale A-H) was given according to the radiographic development, from first appearance of calcification to the closure of the apex. This score was then transformed into a self-weighted maturity score for the dental stages (0-19.3) as presented in the paper. The individual scores were then added giving a total maturity score (0-100). This total maturity score represents the biological maturity of the child and may then be compared with the known chronological age. The total maturity scores of the Hungarian population was plotted against the chronological (real) age, and a curve was fitted using the Lowess method of locally weighted least-square method. Our results show that each population needs its own standards. Hungarian boys and girls are approximately 1 year ahead of their French-Canadian counterparts at the age of 6-8. At older ages, the difference decreases. Similar to other studies, we found high individual variance up to 2 years, in tooth development, in the Hungarian population.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.003 | 0.001 |
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".