Algorithm for Temporomandibular Disorders With Osteopathic Manipulative Therapy: An Expert Consensus
Bibliographic record
Abstract
Objective: The purpose of this study was to create a consensus algorithm for the osteopathic approach to temporomandibular dysfunctions Methods: A conventional Delphi method of at least 3 rounds of questionnaires was carried out by a panel of experts to reach a consensus on a flowchart algorithm for the diagnosis and treatment of temporomandibular disorders with osteopathic manipulative therapy Results: During the 3 rounds, a total of 7 panellists participated. Consensus was reached on 182 items (70.54% = 182/258). The algorithm has a numerical code with which the direction of each option can be followed, and a color code that shows the classification of each of the items (anamnesis, examination, observation, referral, palpation and treatment). The algorithm begins with 4 main categories: psychological aspects, exclusion criteria, physical aspects, and other issues, which are further subdivided into specific items that will be addressed according to the findings obtained during the patient visit. Conclusion: This study created an algorithm for the osteopathic approach to temporomandibular dysfunctions.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".