Claw Hardness of Dairy Cows: Relationship to Water Content and Claw Lesions
Bibliographic record
Abstract
Lameness of dairy cows is a major welfare and economic problem. Degree of hardness of claws may influence chances for injury or for claw lesions, and exposure of claws to moisture may make them soft. To assess the relationship among hardness of the claw horn, quantity and rate of absorption of water, and incidence of claw lesions, 4 experiments were carried out. In the first 3 experiments, we soaked pieces of the claw horn in water for 12 to 24 h. Soaked claws gained weight and became significantly softer, indicating that water was absorbed. One-third of the total water absorbed in 24 h occurred during the first hour. Base of the abaxial and dorsal walls of the claw was harder than the sole, but became softer more rapidly when soaked in water. In the 4th experiment, significant negative correlations were detected between claw hardness of cows and severity of claw lesions, suggesting that cows with softer claws have the most severe claw lesions. Claw horn tissue absorbs water rapidly and claw hardness decreases with moisture content, suggesting that brief exposures to moist surfaces result in claws that absorb water and consequently become softer. The relationship between hardness and claw lesions indicates that cows with softer claws are at greater risk for 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".