The association between oral examination findings and computed tomographic appearance of the equine temporomandibular joint
Bibliographic record
Abstract
BACKGROUND: The temporomandibular joint (TMJ) forms the junction between the maxilla and mandible. Movement of the jaw and resulting masticatory forces have been extensively studied in the horse; however, less is known about the inter-relationship between this joint and oral and dental pathology. OBJECTIVES: To determine the association between specific oral and dental pathologies and anatomical variations of the TMJ imaged with computed tomography (CT) in horses with asymptomatic TMJs. STUDY DESIGN: Retrospective cross-sectional study. METHODS: Horses (n = 201) from three practices with a complete oral examination and skull or upper cervical CT study were reviewed. Age, breed, sex, clinical presentation, oral examination findings, slice width and practice were recorded. Alterations in contour and density of the mandibular condyle, mandibular fossa and intra-articular disc were also documented. Logistic regression, corrected for clustering by practice, was used to determine whether CT anatomical variations were significantly associated with the oral examination findings. RESULTS: Horses categorised as having abnormal TMJs were older than those with normal TMJ. Horses with periodontal disease were less likely to have abnormal TMJ findings compared with horses with no oral pathology. In contrast, horses with infundibular disease were more likely to have TMJ abnormalities. MAIN LIMITATIONS: Due to the cross-sectional nature of the study, it was difficult to establish whether oral pathology preceded TMJ abnormalities. CONCLUSIONS: Despite examining over 200 horses of varying ages, the biological significance of the observed associations between oral, or dental disease and anatomically appreciable temporomandibular joint disorders remains uncertain.
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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 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".