Evaluation of Osteoarthritis in Cats: Novel Information from a Pilot Study
Bibliographic record
Abstract
OBJECTIVE: To describe structural changes associated with osteoarthritis (OA) in cats and to quantify OA-associated disability using functional evaluations. STUDY DESIGN: Cross-sectional pilot study with longitudinal data. ANIMALS: Normal cats (n = 2) and coxofemoral joint OA cats (n = 4) were evaluated by physical examination, radiography, and magnetic resonance imaging (MRI). METHODS: Structural changes related to OA were scored using computed radiographs (CR) and MRI. Functional evaluation consisted of podobarometric gait analyses performed using a pressure-sensitive mattress and motor activity assessments using collar-attached, accelerometer-based activity sensors. RESULTS: Structural scores for the coxofemoral joint OA-related lesions were lower in normal cats than OA cats for MRI (P = .07). Use of MRI allowed for whole-organ assessment of the coxofemoral joint. Pelvic limb peak vertical ground reaction force (PVF) was higher in normal cats than OA cats (P = .10). During the night, motor activity was greater in normal cats than OA cats (P = .04). PVF was positively correlated with mean motor activity (Spearman coefficient [Rho] = 0.83, P = .04) and negatively correlated with age and MRI structural score (Rho = -0.93 and -0.79, P < .01 and .06, respectively). CONCLUSIONS: This study provides the first description of OA-related lesions in cats using MRI. Gait analysis and accelerometry should be considered as objective tools to characterize OA-associated disability, although these assessments were weakly correlated with structural changes.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 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".