Associations between the general condition of culled dairy cows and selling price at Ontario auction markets
Bibliographic record
Abstract
Dairy cows are culled from the herd for a variety of reasons, the most common being fertility problems, low milk production, or udder problems. Disease and injury can contribute to the decision to cull either directly, or indirectly, by causing fertility or production problems, leading to culling. Disease or injury may also affect the cow's ability to handle the stress of transportation and may increase the risk for reduced welfare. The purpose of this study was to determine the general condition of culled dairy cows sold at Ontario auction markets, to quantify the frequency of culled cows in poor condition sold at these auctions, and to determine how this relates to the sale price of the cow. Data were collected on 4,460 culled dairy cows, sold at 3 Ontario auction markets, over a continuous 16-wk study period. Observers assessed the general condition of dairy cows entering the sales ring by recording each individual cow's hock injury score, body condition score (BCS), gait score, and tail score, in accordance with 2017 Canadian proAction Animal Care guidelines. Each cow's body weight, breed, and sale price were also recorded. Results showed that 27.2% of culled cows scored had unacceptable hock injuries, 40.5% had a BCS ≤2, 72.7% had an abnormal gait, and 12.5% had docked tails. Culled cows with a BCS ≤2 sold for $0.20 less/kg compared with those with a BCS >2, which equated to an overall average loss of $117 per cow. Cows with an abnormal gait sold for $0.05 less/kg compared with culled cows with a normal gait, which equated to an overall average loss of $32.45 per cow. There was no difference in the sale price depending on hock injury score or the presence or absence of a full tail. The main issues identified in this study were the high prevalence of low body condition and abnormal gait, indicating that the welfare of these cows may be at risk. Additionally, cows with low BCS or abnormal gait sold for a lower price compared with cows that were in good condition, leading to reduced potential profit for the producer.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".