Recommendations from the International Consensus Workshop: convergence on an orofacial pain taxonomy
Bibliographic record
Abstract
This 2·5-day workshop was organized by the International RDC/TMD Consortium Network of the International Association for Dental Research and the Orofacial Pain Special Interest Group of the International Association for the Study of Pain. Workshop participation was by invitation based on representation within the field, which included the Consortium Network, the Orofacial Pain Special Interest Group, the National Institute for Dental and Craniofacial Research, American Academy of Orofacial Pain, the European Academy of Craniomandibular Disorders, and the International Headache Society; other disciplines included radiology, psychology, ontology, and patient advocacy. The workshop members were divided into workgroups that reviewed core literature describing the properties of the RDC/TMD, provided recommendations for revision, and suggested relevant research directions. The goals of this workshop were to (i) finalize the revision of the RDC/TMD into a Diagnostic Criteria for Temporomandibular Disorders (DC/TMD), which would be more appropriate for routine clinical implementation, (ii) provide a broad foundation for the further development of suitable diagnostic systems for not only TMD but also oro-facial pain as well, and (iii) provide research recommendations oriented towards improving our understanding of TMD and oro-facial pain. This report provides the full description of the workshop and Executive Summary, and it acknowledges the participants and sponsors.
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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 | 0.266 | 0.310 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.013 | 0.009 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.017 | 0.019 |
| Open science | 0.013 | 0.024 |
| Research integrity | 0.021 | 0.032 |
| Insufficient payload (model declined to judge) | 0.013 | 0.007 |
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".