Reliability and validity of Axis I of the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) with proposed revisions*
Bibliographic record
Abstract
The research diagnostic criteria for temporomandibular disorders (RDC/TMD) have been employed internationally since 1992 for the study of temporomandibular muscle and joint disorders (TMD). This diagnostic protocol incorporates a dual system for assessment of TMD for Axis I physical diagnoses as well as Axis II psychological status and pain-related disability. Because the reliability and criterion validity of RDC/TMD had not yet been comprehensively characterised, the National Institute of Dental and Craniofacial Research funded in 2001 the most definitive research to date on the RDC/TMD as a U01 project entitled, 'Research Diagnostic Criteria: Reliability and Validity'. The results of this multi-site collaboration involving the University of Minnesota, the University of Washington, and the University at Buffalo were first reported at a pre-session workshop of the Toronto general session of the International Association of Dental Research on 2 July 2008. Summaries of five reports from this meeting are presented in this paper including: (i) reliability of RDC/TMD Axis I diagnoses based on clinical signs and symptoms; (ii) reliability of radiographic interpretations used for RDC/TMD Axis I diagnoses; (iii) reliability of self-report data used for RDC/TMD Axis I diagnoses; (iv) validity of RDC/TMD Axis I diagnoses based on clinical signs and symptoms; and (v) proposed revisions of the RDC/TMD Axis I diagnostic algorithms.
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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 | 0.039 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".