White Matter Diffusion Properties in Chronic Temporomandibular Disorders: An Exploratory Analysis
Bibliographic record
Abstract
Objective: To determine differences in diffusion metrics in key white matter (WM) tracts between women with chronic temporomandibular disorders (TMDs) and age- and sex-matched healthy controls. Design: Cross sectional study compared diffusion metrics between groups and explored their associations with clinical variables in subjects with TMDs. Methods: In a total of 33 subjects with TMDs and 33 healthy controls, we performed tractography to obtain diffusion metrics (fractional anisotropy [FA], mean diffusivity [MD], radial diffusivity [RD], and axial diffusivity [AD]) from the cingulum near the cingulate gyrus (CGC), the cingulum near the hippocampus (CGH), the fornix, the anterior limb of the internal capsule (ALIC), the posterior limb of the internal capsule (PLIC), and the uncinate fasciculus (UF). We compared diffusion metrics across groups and explored the relationships between diffusion metrics and clinical measures (pain chronicity and intensity, central sensitization, somatization, depression, orofacial behavior severity, jaw function limitations, disability, and interference due to pain) in subjects with TMDs. Results: We observed differences in diffusion metrics between groups, primarily in the right side of the brain, with the right CGC having lower FA and the right UF having lower FA and higher MD and RD in subjects with TMDs compared to healthy controls. No clinical measures were consistently associated with diffusion metrics in subjects with TMDs. Conclusion: The UF showed potential microstructural damage in subjects with TMDs, but further studies are needed to confirm any associations between diffusion changes and clinical measures.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".