Growing Beagles and Foxhound-Boxer-Ingelheim Labrador Retriever mixed breeds show a forelimb-dominated gait and a cranial shift in weight support over time during a kinetic gait analysis
Bibliographic record
Abstract
OBJECTIVE: To collect kinetic gait reference data of dogs of 2 breeds in their growth period during walking and trotting gait, to describe their development, and to investigate the weight support pattern over time. ANIMALS: 8 Foxhound-Boxer-Ingelheim Labrador Retriever mixed breeds and 4 Beagles. PROCEDURES: Ground reaction force variables (GRFs), peak vertical force and vertical impulse, and temporal variables (TVs) derived therefrom; time of occurrence; and stance times were collected. Body weight distribution (BWD) was evaluated. Six measurements, each containing 1 trial in walking and 1 trial in trotting gait, were taken at age 10, 17, 26, 34, 52, and 78 weeks. The study period started July 17, 2013 and lasted until October 7, 2015. Area under the curve with respect to increase was applied. The difference of area under the curve with respect to increase values between breeds and gaits was analyzed using either the t test or the Mann-Whitney test. Generalized mixed linear models were applied. RESULTS: Significant differences in gait and breed comparisons were found. Growing dogs showed a forelimb-dominated gait. The development of GRF and TV values over the study period were described. CLINICAL RELEVANCE: Reference values for GRFs, TVs, and BWDs in growing dogs were given. A cranial shift in weight support over time was found during trotting gait. Smaller, younger dogs walked and trotted more inconsistently.
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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".