Histologic assessment of age-related changes in the temporomandibular joints of horses
Bibliographic record
Abstract
OBJECTIVE: To describe histologic changes in the temporomandibular joints (TMJs) of horses of various ages. SAMPLE: 22 TMJs from cadavers of 11 horses. PROCEDURES: Horses were categorized into 3 age groups (group 1, 2 to 10 years old [n = 3]; group 2, 11 to 20 years old [3]; and group 3, > 20 years old [5]). Each TMJ was sectioned into 5-mm slices, preserved in formalin, decalcified in formic acid, and routinely processed for histologic analysis. Joints were systematically assessed by use of previously described methods. Multilevel mixed-effects models were used to examine the data. RESULTS: The number of changes was significantly fewer and degree of changes was significantly less within the TMJs of group 1 horses, compared with those of group 3 horses. Comparison among groups revealed that the combination of temporal and mandibular scores for group 1 was significantly lower than for groups 2 or 3. Disk score did not differ significantly between groups 1 and 2, but disk scores of groups 1 and 2 were significantly lower than the disk score of group 3. CONCLUSIONS AND CLINICAL RELEVANCE: The assessed lesions were associated with osteoarthritis, and they accumulated in the TMJs as horses aged. In the absence of signs of pain manifested as changes in mastication, behavior, or performance, it would be difficult to determine the point at which accrued pathological changes represented the onset of clinically important osteoarthritis of the TMJs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.001 | 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".