Expanding the taxonomy of the diagnostic criteria for temporomandibular disorders
Bibliographic record
Abstract
There is a need to expand the current temporomandibular disorders' (TMDs) classification to include less common but clinically important disorders. The immediate aim was to develop a consensus-based classification system and associated diagnostic criteria that have clinical and research utility for less common TMDs. The long-term aim was to establish a foundation, vis-à-vis this classification system, that will stimulate data collection, validity testing and further criteria refinement. A working group [members of the International RDC/TMD Consortium Network of the International Association for Dental Research (IADR), members of the Orofacial Pain Special Interest Group (SIG) of the International Association for the Study of Pain (IASP), and members from other professional societies] reviewed disorders for inclusion based on clinical significance, the availability of plausible diagnostic criteria and the ability to operationalise and study the criteria. The disorders were derived from the literature when possible and based on expert opinion as necessary. The expanded TMDs taxonomy was presented for feedback at international meetings. Of 56 disorders considered, 37 were included in the expanded taxonomy and were placed into the following four categories: temporomandibular joint disorders, masticatory muscle disorders, headache disorders and disorders affecting associated structures. Those excluded were extremely uncommon, lacking operationalised diagnostic criteria, not clearly related to TMDs, or not sufficiently distinct from disorders already included within the taxonomy. The expanded TMDs taxonomy offers an integrated approach to clinical diagnosis and provides a framework for further research to operationalise and test the proposed taxonomy and diagnostic criteria.
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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 | 0.030 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.021 | 0.011 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 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".