Effect of dog breed and body conformation on vertical ground reaction forces, impulses, and stance times
Bibliographic record
Abstract
OBJECTIVES: To assess whether fully normalised vertical ground reaction forces and stance times obtained at a trot depend on dog breed or body conformations. METHODS: Peak vertical forces (PVF), vertical impulses (VI), stance times (ST), and ratio of forelimb impulse to total impulse (RVI) of 54 dogs of seven different breeds were normalised to body weight and body size according to the theory of dynamic similarity, and were tested for differences between breeds. Breeds were Borzoi, Bernese Mountain dog, Great Dane, Labrador Retriever, Landseer, Rhodesian Ridgeback, and Rottweiler. Body length ratio (BLR) and body mass index (BMI) were also compared between breeds. RESULTS: Significant differences between breeds were found for the normalised forelimb PVF, VI and ST, and hindlimb PVF. Looking at individual breeds, it was most evident that Borzois had a lower forelimb VI, and a higher hindlimb PVF than the other breeds. This resulted in Borzois having a lower RVI compared to other dogs, indicating a more caudally located centre of gravity. Only a few differences in gait parameters were found between other dog breeds. The BMI was significantly lower in Borzois than in other breeds, but was otherwise not associated with gait parameters. CLINICAL SIGNIFICANCE: Force plate data of dogs of different breeds are not necessarily comparable, even after full normalisation to body weight and body size. Group comparisons should only be made when the groups consist of breeds with similar body conformations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".