Herd-level risk factors for hock injuries in freestall-housed dairy cows in the northeastern United States and California
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The aim of this study was to investigate the associations between management and facility design factors and the prevalence of hock injuries in high-producing dairy cows in 76 freestall herds in the northeastern United States (NE-US; Vermont, New York, Pennsylvania) and California (CA). One group of high-production multiparous cows was monitored on each farm, and data on management, facility and stall design, and the conditions of the hocks were collected. Focal cows [n=38 ± 3 (mean ± standard deviation)] were evaluated for hock injuries using a 3-point scale (where 1=healthy and 3=evidently swollen or severe injury). Measures associated with the proportion (logit-transformed) of cows having injuries (score ≥ 2) or severe injuries (score=3) at the univariable level were submitted to multivariable general linear models. In NE-US, overall hock injuries increased with the percentage of stalls with fecal contamination [odds ratio (OR)=1.26; 95% confidence interval (CI)=1.02-1.54, for a 10% increase], and with the use of sawdust as bedding (OR=3.47; CI=1.14-10.62), and decreased with deep bedding (i.e., at least 10 cm depth of any type of bedding; OR=0.05; CI=0.02-0.14), use of sand as bedding (OR=0.06; CI=0.02-0.15), bedding dry matter (DM) ≥ 83.9% (OR=0.08; CI=0.03-0.20), and access to pasture during the dry period (OR=0.17; CI=0.05-0.53). When these variables were submitted to a multivariable model, the presence of deep bedding was the only factor that remained significant, explaining 54% of the variation in overall injuries. Severe hock injuries increased with the use of automatic scrapers (OR=2.29; CI=1.11-4.71) and the percentage of stalls with fecal contamination (OR=1.14; CI=1.00-1.31, for a 10% increase), and decreased with sand bedding (OR=0.22; CI=0.10-0.49), deep bedding (OR=0.24; CI=0.11-0.52), bedding DM ≥ 83.9% (OR=0.28; CI=0.14-0.58), and access to pasture during the dry period (OR=0.42; CI=0.18-0.97). The final multivariable model, which explained 36% of the variation in severe hock injuries, included the use of automatic scrapers and deep bedding. In CA, stall stocking density (OR=1.41; CI=1.00-2.01, for a 10% increase) and poor bedding maintenance (OR=1.08; CI=1.01-1.16, for a 2.5-cm decrease in depth of deep-bedded stalls) were associated with an increase of overall and severe hock injuries, respectively. Deep-bedded and well-maintained stalls reduce the risk of hock injuries. Regional variation in risk factors for these injuries should be considered when formulating on-farm recommendations.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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 it