Reliability in Mandibular Movement Evaluation Using Photogrammetry in Patients With Temporomandibular Disorders
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to propose a quantitative evaluation for mandibular opening-closing movement asymmetries and to verify the intraexaminer and interexaminer reliability using photogrammetry in individuals with and without myogenic temporomandibular disorders. METHODS: Forty-nine female participants between ages 18 and 40 were enrolled in this study. They were assigned to 2 different groups: a temporomandibular disorder group, (n = 25; 28.1 ± 3.6 years) and an asymptomatic group (n = 24; 25.6 ± 5.1 years). Data were collected through photogrammetry using Corel Draw X3 software (Corel Corp, Ottawa, Ontario, Canada) for angle measurements. Reliability analysis was done on the total sample, and the photographs were obtained by a singular examiner on 2 occasions (intraexaminer) 1 month apart and from measurement made by another examiner (interexaminer) on different days. The intraclass correlation coefficient (ICC) was applied with a significance level of 5%. RESULTS: The photogrammetry had excellent intrarater and inter-rater reliability for the evaluation of opening and closing movements of the jaw (intrarater: opening ICC = 0.99; closing ICC = 0.98; inter-rater: opening ICC = 0.89 and closing ICC = 0.82). Photogrammetry also demonstrated excellent intra- and inter-rater reliability in the evaluation of head posture (intra-rater: head deviation ICC = 0.96; head position ICC = 0.75; inter-rater: head deviation ICC = 0.98; head position ICC = 0.98). CONCLUSION: Under these experimental conditions, most angular values presented excellent intra- and interexaminer reliability.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".