Assessment of dental maturity of Brazilian children aged 6 to 14 years using Demirjian's method
Bibliographic record
Abstract
UNLABELLED: Dental maturity, often expressed as dental age, is an indicator of the biological maturity of growing children. A method for the assessment of dental maturity was first described by Demirjian, and is widely used and accepted, mainly because of its ability to compare different ethnic groups. This is possible, as the maturity scoring system proposed by the method is universal in application, although the conversion to dental age depends on the population considered. OBJECTIVES: The aim of this study was to apply Demirjian's method to Brazilian children aged 6-14 years in order to obtain dental maturity curves for each sex, to compare this data with that obtained by Demirjian, and to determine whether there is a significant correlation between dental maturity and body mass index. METHODS: We retrospectively reviewed the orthopantomograms, height and weight measurements of 689 healthy children. Curves of dental maturity of males and females were constructed. RESULTS: When compared to the French-Canadian sample of Demirjian, Brazilian males and females were 0.681 years and 0.616 years, respectively, more advanced in dental maturity. There was no significant correlation between dental maturity and body mass index.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 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".