Fitness for transport of cull dairy cows at livestock markets
Bibliographic record
Abstract
Cows are regularly removed from dairy herds and sold at livestock markets. Many cows are removed because of health problems, and their fitness for transport may vary because of seasonal variation, delayed or poor on-farm culling decisions, injuries during transport, and other factors. However, many dairy producers lack feedback about the condition of their cows during the marketing process and how cow condition influences sale price. This study evaluated the condition of cull dairy cows sold at livestock markets, tested how changing demand for milk influenced fitness for transport, and quantified how cow condition affected the price paid. For 12 mo, 2 livestock markets in British Columbia, Canada, were visited during 137 auction events when cull dairy cows were sold; 3 trained assessors observed 6,263 cull dairy cows while they were marketed in a sale ring. Observers recorded the cows' body condition score (BCS), locomotion score (LS), udder condition, quality defects (e.g., injuries, illness), and price. Logistic regression was used to test how month-to-month changes in demand for milk affected cows' fitness for transport, and a linear mixed model assessed how the animals' condition influenced the price. About 10% of the cows were thin (BCS ≤2), 7% were severely lame (locomotion score ≥4), 13% had engorged or inflamed udders, and 6% had other quality defects including abscesses, injuries, and signs of sickness (e.g., pneumonia). Cows culled during months with increased milk demand had much higher odds of poor fitness for transport (odds ratio 8.6, 95% confidence interval: 4.02-18.22). The price was most reduced if cows were thin (BCS ≤2) or visibly sick (-$0.63 ± 0.01/kg and -$0.56 ± 0.02/kg, respectively). Prices were reduced to a lesser degree by locomotion score ≥4 (-$0.35 ± 0.02/kg) and by udder condition (udder inflammation; -$0.30 ± 0.02/kg). Overall fitness for transport reduced the price by $0.51 ± 0.01/kg. In summary, about 30% of the cows sold at livestock markets had poor fitness for transport, which was partially influenced by increased milk demand and resulted in reduced market prices.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".