Restorative thresholds for primary and permanent molars in children: French dentist decisions
Bibliographic record
Abstract
BACKGROUND: Worldwide, numerous surveys have investigated practices and knowledge about caries management in adults, but few are available for children. AIM: The present cross-sectional survey aimed to assess the restorative thresholds (RTs) in primary and permanent molars in children used by a population of dentists treating children and practicing in France. DESIGN: The study population consisted of French dentists treating children (Fr-DTCs) who were registered in the French Society of Pediatric Dentistry (n = 250). A specific questionnaire was developed. Descriptive and statistical analyses were performed. RESULTS: Response rate was 80.4% (n = 201). Considering that an appropriate RT is at the stage of a moderate lesion (occlusal: International Caries Detection and Assessment System 4; approximal: lesion involving the external third of dentine), more than 50% of respondents showed a tendency for iatrogenic treatment, except for occlusal carious lesions in primary molars. Inappropriate invasive strategies were more often reported for occlusal lesions in permanent than primary molars. Moreover, for both molar types, these inappropriate RTs were more often chosen for approximal than occlusal lesions. CONCLUSIONS: The present survey suggested that Fr-DTCs tend to overtreat in terms of caries management in both primary and permanent molars.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".