An investigation into the practices of dairy producers and veterinarians in dehorning dairy calves in Ontario.
Bibliographic record
Abstract
The objective of this survey was to describe the current state of dehorning practices by dairy producers and veterinarians in Ontario and to identify opportunities to improve on existing practices. Two hundred and seven producers and 65 veterinarians completed a survey on dehorning practices during the summer of 2004. Seventy-eight percent of dairy producers dehorn their own calves; 22% use local anesthetics. Veterinarians dehorn calves for 31% of dairy clients; 92% use local anesthetics. Pain management was the most common reason for use of local anesthetics for both groups, while time (veterinarians) and time and cost (producers) were the most common reasons for lack of use. Producers who used local anesthetics were 6.5 times more likely to have veterinary involvement in their dehorning decisions. Thirteen percent of producers were unaware of the options for pain management. These results suggest that veterinarians should take the initiative to educate their clients about the options for pain management.
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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 | 0.002 | 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 | 0.000 | 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".