The biomechanics of working dog locomotion I: Steady-state trotting
Bibliographic record
Abstract
The biomechanics of steady-state locomotion in different breeds of working dog is understudied, despite widespread use of these animals in multiple industries. It is unknown how kinematic and kinetic parameters vary between breeds and how these variations are potentially related to inter-breed variations in morphology. Here, gross morphology and trotting locomotion within a cohort of 27 Labrador Retrievers (“Labradors”), shepherd breeds (“Shepherds”) and spaniel breeds (“Spaniels”) were compared using motion capture, force plates and biomechanical modelling. Evidence for slight positive allometric scaling of limb and body lengths was found between the breeds, with relatively longer lengths seen in Shepherds compared to Spaniels. Significant between-breed differences in raw spatiotemporal parameters were found with the larger Shepherds trotting with greater velocities, stride lengths and ground reaction forces than the smaller breeds, although many of these factors scaled with isometry with respect to body mass when accounting for variations in trotting speed. However, gait cycle times and stride lengths do not scale isometrically with body size, which, taken together with significant differences in flexion-extension joint angles and moments, suggest dynamic similarity during trotting is unlikely between these breeds. Overall, these findings highlight specific differences in the biomechanics of steady-state trotting locomotion between working dog breeds despite their somewhat geometrically similar gross body proportions. This suggests that not only should locomotion databases for individual breeds exist for future canine research, but also that breed-specific considerations should be adopted to maximise the health and welfare of these dogs in working practices, such as load-carrying tasks.
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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 | 0.000 | 0.000 |
| 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 | 0.002 | 0.001 |
| 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".