Validity and Reproducibility of ICDAS II in Primary Teeth
Bibliographic record
Abstract
The aim of this in vitro study was to assess the validity and reproducibility of the ICDAS II (International Caries Detection and Assessment System) criteria in primary teeth. Three trained examiners independently examined 112 extracted primary molars, ranging from clinically sound to cavitated, set up in groups of 4 to mimic their anatomical positions. The most advanced caries on the occlusal and approximal surfaces was recorded. Subsequently the teeth were serially sectioned and histological validation was undertaken using the Downer and Ekstrand-Ricketts-Kidd (ERK) scoring systems. For occlusal surfaces at the D(1)/ERK(1) threshold, the mean specificity was 90.0%, with a sensitivity of 75.4%. For approximal surfaces, the specificity and sensitivity were 85.4 and 66.4%, respectively. For occlusal surfaces at ICDAS code > or =3 (ERK(3) threshold), the mean specificity and sensitivity were 87.0 and 78.1%, respectively. For approximal surfaces, the equivalent values were 90.6 and 75.3%. At the D(3) threshold for occlusal surfaces, the mean specificity and sensitivity were 92.8 and 63.1%, and for approximal surfaces 94.2 and 58.3%, respectively. Mean intraexaminer reproducibility (Cohen's kappa) ranged from 0.78 to 0.81 at the ICDAS code > or =1 cut-off and at the ICDAS code > or =3 cut-off from 0.74 to 0.76. Interexaminer reproducibility was lower, ranging from 0.68 to 0.70 at the ICDAS code > or =1 cut-off and from 0.66 to 0.73 at the ICDAS code > or =3 cut-off. In conclusion, the validity and reproducibility of the ICDAS II criteria were acceptable when applied to primary molar teeth.
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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 | 0.024 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".