Development of Two Innovative Performance-Based Objective Measures in Feline Osteoarthritis: Their Reliability and Responsiveness to Firocoxib Analgesic Treatment
Bibliographic record
Abstract
The metrological properties of two performance-based outcome measures of feline osteoarthritis (OA), namely Effort Path (Path) and Stairs Assay Compliance (Stairs), were tested. Cats naturally affected by OA (n = 32) were randomly distributed into four groups (A: 0.40, B: 0.25, C: 0.15, or D: 0.00 mg firocoxib/kg bodyweight) and assessed during baseline, treatment, and recovery periods. For Path, from an elevated walking platform, the cats landed on a pressure-sensitive mattress and jumped up onto a second elevated platform. Analysis included velocity, time to completion, peak vertical force (PVF), and vertical impulse. For Stairs, the number of steps and time to completion were recorded for 16 steps up and down in a 4 min period. Reliability was moderate to very good for Path and poor to good for Stairs. Different normalization methods are described in the manuscript. The placebo group remained stable within-time in Path, whereas treated cats trotted faster on the ramp (p < 0.0001), improved their PVF (p < 0.018) and completed the task quicker (p = 0.003). The percentage of cats completing the Stairs finish line was higher under treatment (p < 0.036), with huge effect size, the placebo group results being stable within-time. Both are promising performance-based outcome measures to better diagnose and manage feline OA pain.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".