Depicting Errors in Clinical Decisions for Posterior Proximal Enamel Caries Lesions in Permanent Teeth Using the Fact Box Format
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: To depict restorative treatment recommendations of US dentists for posterior proximal enamel caries lesions detected with bitewing radiographs in permanent teeth. METHODS: The Fact Box format was utilized to depict the probabilities of restorative treatment recommendations made by US dentists for posterior proximal enamel caries lesions detected with bitewing radiographs in permanent teeth. Four case scenarios were considered, including patients at low caries risk versus those at high caries risk for two proportions (10% versus 38%) of proximal enamel caries lesions with external surface cavitation. RESULTS: The Fact Box showed that the decision to restore posterior proximal enamel caries lesion was more likely to be an incorrect decision (61-91%) in the four case scenarios considered. Meanwhile, the decision to not provide restorative treatment for posterior proximal enamel caries lesion was less likely to be erroneous (9-37%) in the four case scenarios considered. CONCLUSION: Using the Fact Box to depict restorative decision-making for posterior proximal enamel caries lesions in permanent teeth may improve communication of decisional probabilities and reduce restorative overtreatment.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it