PSXI-29 Comparison of temporal-spatial and pressure gait analysis between resting and exercised Labrador retrievers
Bibliographic record
Abstract
Abstract Exercise-induced muscle damage and subsequent inflammation and soreness are frequently studied topics in both human and animal trials. Gait analysis using a commercial mat system is a newer technology that identifies the temporal and spatial qualities of a subject’s gait. Gait analysis in healthy canines, especially in an exercise model, has been infrequently studied. Our objectives were to compare gait analysis metrics between exercised and non-exercised dogs, to identify which parameters were most impacted by running exercise, and to identify the ideal time to perform gait analysis post-exercise. Twenty-four Labrador retrievers were used in this trial, with 12 untrained dogs performing one 5km run, and 12 untrained dogs providing a resting comparison. All dogs were gaited using a Gait4Dogs (CIR Systems, Inc) pressure walkway system at baseline, 30min post-run, 3h post-run, and 24h post-run. For pressure measurements, no significant differences were found in resting dogs. In exercised dogs, number of activated sensors was significantly lower 30min post-run compared to baseline (p=0.05). Pressure time was significantly faster 30min post-run compared to 3h post-run (p=0.007), indicating discomfort during the walk. For spatial measurements, no significant differences were found in resting dogs. In exercised dogs, swing% was significantly lower in front limbs at 30min post-run compared to baseline (p=0.001) and in hindlimbs at 30min post-run compared to 3h post-run and 24h post-run (p=0.001), indicating reduced flexion. Stance% was significantly higher in front limbs at 30min post-run compared to all other timepoints (p=0.001) and in hindlimbs at 30min post-run compared to 3h post-run and 24h post-run (p=0.001). Stance time and step time were significantly lower at 3h post-run compared to 30min post-run and 24h post-run (p=0.001;p=0.006), indicating discomfort during the walk. In summary, untrained Labrador retrievers had a significantly affected gait primarily thirty minutes and three hours after exercise compared to resting dogs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".