Concurrent Validation of MI-CAT(V), a Clinical Metrology Instrument for Veterinarians Assessing Osteoarthritis Pain in Cats, through Testing for Firocoxib Analgesic Efficacy in a Prospective, Randomized, Controlled, and Blinded Study
Bibliographic record
Abstract
Veterinarians face the lack of a rapid, reliable, inexpensive, and treatment-sensitive metrological instrument reflecting feline osteoarthritis (OA) pain. The Montreal Instrument for Cat Arthritis Testing, for Use by Veterinarians (MI-CAT(V)) has been refined in 4 sub-sections, and we proposed its concurrent validation. Cats naturally affected by OA (n = 32) were randomly distributed into 4 groups of firocoxib analgesic (Gr. A: 0.40; B: 0.25; C: 0.15, and P: 0.00 mg/kg bodyweight). They were assessed during Baseline, Treatment, and Recovery periods using MI-CAT(V) and objective outcomes (effort path, stairs assay compliance, and actimetry). The MI-CAT(V) total score correlated to the effort path and actimetry (RhoS = −0.501 to −0.453; p < 0.001), also being sensitive to treatment responsiveness. The pooled treatment group improved its total, gait, and body posture scores during Treatment compared to the Baseline, Recovery, and placebo group (p < 0.05). The MI-CAT(V) suggested a dose-(especially for Gr. B) and cluster-response. Cats in the moderate and severe MI-CAT(V) clusters responded to firocoxib with a remaining analgesic effect, while the mild cluster seemed less responsive and experienced a negative rebound effect. The MI-CAT(V) was validated for its OA pain severity discriminatory abilities and sensitivity to firocoxib treatment, providing a new perspective for individualized care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".