Hoof Discomfort Changes How Dairy Cattle Distribute Their Body Weight
Bibliographic record
Abstract
Lameness is a costly and widespread health and welfare problem in intensive dairy production, and reliable automated methods to detect lameness are needed. Lameness may be detected through the measurement of how cattle distribute their weight among their 4 legs, but this requires an understanding of how cattle redistribute their weight in response to pain in one or more limbs. In 3 experiments, 13, 12, and 15 Holstein dairy cows were trained to stand on a platform that measured the weight placed on each limb. We replaced the soft rubber surface under either 1 or 2 hooves with an uncomfortable concrete surface. Cows placed less weight on a back hoof that was placed on an uncomfortable surface, and they redistributed the majority of the weight onto the contralateral back hoof but did not change the distribution of weight on their front hooves. When the same surface was placed under a front hoof, cows placed less weight on that hoof and placed more weight on the contralateral front hoof and the ipsilateral back hoof. The variation in weight the cow placed on both contralateral hooves increased when one of the hooves was on the uncomfortable surface. Cows placed more weight on the back hooves when both front hooves were standing on uncomfortable surfaces, although no change was observed when back hooves were on uncomfortable surfaces. Dairy cows remove weight from a limb in response to limb discomfort and redistribute this weight primarily to the contralateral limb. The variation in weight over time applied to a pair of contralateral limbs increases in response to discomfort in one hoof. Cows have only limited ability to shift weight from front to back. Measures of weight distribution may provide useful on-farm techniques for the detection of lameness.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".