Comparison of trot kinetics between dogs with stifle or hip arthrosis
Bibliographic record
Abstract
The purposes of this study were: 1) to describe and compare the trotting gait of normal and lame dogs secondary to stifle (GONOA) or hip (COXOA) osteoarthritis (OA) using multiple ground reaction forces (GRF) parameters, and 2) to pinpoint any characteristic in gait profile ('signatures') which could help to discriminate a lameness secondary to GONOA or COXOA. Fifty-one large breed dogs with OA (19 GONOA, 32 COXOA) and 22 normal dogs were included in the study. The vertical and cranio-caudal (braking-propelling) GRF were collected. The total stance time, and for each orthogonal vector, the peak force, impulse, time to peak, and the rate of limb loading were recorded. Vertical and craniocaudal forces were found to be significantly decreased in both OA groups compared to normal dogs. Vertical, cranial and caudal limb loading were also most often lower for both OA groups. In addition, the vertical and cranial forces were significantly lower in dogs with GONOA compared to COXOA and normal dogs. This study has demonstrated that, at a trotting gait, OA dogs secondary to GONOA and COXOA load their affected limb, brake and propel earlier during the stance phase, but generally with less magnitude than normal dogs. Dogs affected by GONOA also present more severe gait alterations than dogs with COXOA. The vertical and braking specific GRF alterations described may be kinetic 'signatures' linked more to lame dogs secondary to GONOA versus COXOA. Finally, this study has also provided useful baseline GRF data for further clinical and research investigations.
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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 | 0.001 |
| 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 | 0.000 | 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".