DIAGNOdent--an adjunctive diagnostic method for caries diagnosis in epidemiology.
Bibliographic record
Abstract
UNLABELLED: The DIAGNOdent system is intended as an aid to caries detection and has undergone extensive investigation in experimental and clinical studies. Its applicability for epidemiological purposes has yet to be evaluated. The Objective of the present study was to evaluate the DIAGNOdent system under field conditions. BASIC RESEARCH DESIGN: The subjects comprised a sub-sample from an on-going epidemiological study. PARTICIPANTS AND CLINICAL SETTING: In 39 individuals, 97 sites were visually identified as possibly carious: 42 occlusal, 13 lingual, 19 buccal and 23 approximal sites. MAIN OUTCOME MEASURES: Three DIAGNOdent measurements were taken at each site under varying conditions: (1) naturally wet, (2) dried, and (3) polished and dried surfaces. Three sets of measurements were obtained and compared by intra-class correlation and paired sample t-tests. RESULTS: All correlation coefficients were > 0.9. There was a systematic difference between mean scores from naturally wet sites (without cleaning) and from either dried, or polished and dried sites. The difference was marginal and did not impact on the threshold for recording sites as carious. In two subjects, high unexpected values were recorded on sound sites prior to actual measurements, i.e. during establishment of a standard value for a sound site. The overall findings were not affected by these values, as they were consistently high in all three measurements. CONCLUSIONS: The DIAGNOdent system performed satisfactorily under different measurement conditions. The present study indicates that the DIAGNOdent system would be applicable in field studies, provided consistent study conditions are maintained and unexpected values are interpreted with caution.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".