Hoof Pathologies Influence Kinematic Measures of Dairy Cow Gait
Bibliographic record
Abstract
To explore how hoof pathologies affect the gait of dairy cattle, we studied gait profiles of cows with no visible injuries (n = 17), sole lesions (n = 14), and sole ulcers (n = 7). Video recordings of dairy cows were digitized using motion analysis software to calculate 6 stride variables for each hoof. Compared with cows with sole ulcers, healthy cows walked faster (1.11 +/- 0.03 vs. 0.90 +/- 0.05 m/s, mean +/- SEM), had shorter stride durations (1.26 +/- 0.03 vs. 1.48 +/- 0.05 s), and longer strides (139.5 +/- 2.1 vs. 130.0 +/- 3.2 cm). Percentage of triple support in the gait cycle (time when cattle were supported by 3 legs) more than doubled for cows with sole ulcers compared with healthy cows (42 vs. 18%). Gait differences were likely due to cows reducing the load on an affected leg. Few differences were detected between healthy cows and those with sole lesions, perhaps because of variation in number, severity, and location of injuries. Kinematic gait analysis is a promising approach in understanding how hoof pathologies affect dairy cow gait.
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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 | 0.001 | 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".