Examiner training and reliability in two randomized clinical trials of adult dental caries
Bibliographic record
Abstract
OBJECTIVES: This report describes the training of dental examiners participating in two dental caries clinical trials and reports the inter- and intra-examiner reliability scores from the initial standardization sessions. METHODS: Study examiners were trained to use a modified International Caries Detection and Assessment System II system to detect the visual signs of non-cavitated and cavitated dental caries in adult subjects. Dental caries was classified as no caries (S), non-cavitated caries (D1), enamel caries (D2), and dentine caries (D3). Three standardization sessions involving 60 subjects and 3,604 tooth surface calls were used to calculate several measures of examiner reliability. RESULTS: The prevalence of dental caries observed in the standardization sessions ranged from 1.4 percent to 13.5 percent of the coronal tooth surfaces examined. Overall agreement between pairs of examiners ranged from 0.88 to 0.99. An intra-class coefficient threshold of 0.60 was surpassed for all but one examiner. Inter-examiner unweighted kappa values were low (0.23-0.35), but weighted kappas and the ratio of observed to maximum kappas were more encouraging (0.42-0.83). The highest kappa values occurred for the S/D1 versus D2/D3 two-level classification of dental caries, for which seven of the eight examiners achieved observed to maximum kappa values over 0.90. Intra-examiner reliability was notably higher than inter-examiner reliability for all measures and dental caries classifications employed. CONCLUSION: The methods and results for the initial examiner training and standardization sessions for two large clinical trials are reported. Recommendations for others planning examiner training and standardization sessions are offered.
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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 | 0.269 | 0.352 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".