Dental maturity of Caucasian children in the Indianapolis area
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to compare chronologic and dental age using Demirjian's method. \nMETHODS: Two hundred and fifty-seven panoramic radiographs of healthy 5- to 17.5-year-old Caucasian children in the Indianapolis area were evaluated using Demirjian's 7 tooth method. \nRESULTS: The intraclass correlation coefficient (ICC) for agreement with Demirjian was 0.94 (95% confidence interval [CI]: 0.87, 0.97). The ICC for repeatability of the investigator was 0.97 (95% CI=0.95, 0.99). Calculated dental age was significantly greater than chronologic age by 0.59 years (P<.001). There was no significant difference in the mean difference in ages between sexes (P=.73). Medicaid subjects had a significantly higher (P<.001) mean difference (0.82 years) than private insurance subjects (0.32 years). There was a significant negative correlation between the chronologic age and the difference in ages (r=-0.29, P<.001). Overweight (P<.001) and obese (P=.004) subjects were significantly more dentally advanced than normal (P=.35) and underweight (P=.42) subjects. \nCONCLUSIONS: Demirjian's method has high inter- and intraexaminer repeatability. Caucasian children in the Indianapolis area are more advanced dentally than the French-Canadian children studied by Demirjian. Difference between dental age and chronologic age varies depending on the age of the child, socioeconomic status, 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".