The International Caries Classification and Management System (ICCMS™) An Example of a Caries Management Pathway
Bibliographic record
Abstract
The International Caries Classification and Management System (ICCMS™) is a comprehensive set of clinical protocols that address all diagnostic, preventive and restorative decisions necessary “to preserve tooth structure and restore only when indicated,” which is the mission adopted at the Temple University Caries Management Pathways workshop, in 2012 [ 1 ]. The foundation for ICCMS™ is based on extensive critical analyses, research, and clinical feedback on the best approaches to move away from the mechanical or restorative care that has been followed around the world, towards a system where prevention is emphasized, initial caries lesions are prevented from progressing (controlled), and moderate or extensive caries lesions are restored with the goal of preserving, as much as possible, natural tooth structure [ 2 ]. This chapter will describe the scientific, and clinical management protocols that have been developed over the last several years by over 70 cariologists, epidemiologists, and clinicians.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".