COMPUTED TOMOGRAPHIC APPEARANCE OF THE TEMPOROMANDIBULAR JOINT IN 1018 ASYMPTOMATIC HORSES: A MULTI‐INSTITUTION STUDY
Bibliographic record
Abstract
Published descriptions of nonseptic arthritis of the equine temporomandibular joint (TMJ) are rare and large studies investigating variations in the TMJ for asymptomatic horses are lacking. The objectives of this cross-sectional, retrospective, multi-institutional study were to describe anatomical variations in the TMJ detected using computed tomography (CT) in an equid population asymptomatic for TMJ disease and determine whether these variations were associated with patient signalment, reason for CT examination, or CT slice width. Medical records at eight hospitals were searched for horses that had head/neck CT scans and no clinical signs of TMJ disease. Age, breed, sex, clinical presentation, and CT slice width data were recorded. Alterations in CT contour and density of the mandibular condyles, mandibular fossae, and TMJ intra-articular discs were described for each horse. Generalized logistic regression was used to test associations between anatomical variations and horse age. A total of 1018 horses were sampled. Anatomical variations were found in TMJ CT images for 40% of horses and 29% of joints. These were dichotomous with regard to age. Horses <1 year old commonly had alterations in the shape and density of the mandibular condyle. Older horses commonly had spherical hypodensities within the mandibular condyles consistent with bone cysts; and hyperdense regions of the intra-articular disc consistent with dystrophic mineralization. Findings indicated that TMJ anatomic variations were common in CT images of younger and older horses asymptomatic for TMJ disease. Future studies are needed to more definitively characterize these CT variations using gross pathology and histopathology.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".