Pain in the weeks following surgical and rubber ring castration in dairy calves
Bibliographic record
Abstract
Many male dairy calves are castrated when reared for beef production, but for dairy breeds the assessment of the longer-lasting pain associated with this procedure has received little scientific attention. In this study we assessed 2 methods: surgical (n = 10 calves) and rubber ring (n = 11). All calves were castrated at 28 d of age using multimodal pain control. During the 8 wk that followed, we recorded wound healing, local inflammation, body weight, milk and calf starter intake, lying time, and wound-directed behavior. Surgical wounds were fully healed on average 4 wk after the procedure, but only 1 calf in the rubber ring treatment fully healed within the 8-wk study. Inflammation was greater after rubber ring castration; skin temperature in the area around the lesion was 1.7 ± 0.35°C (mean ± standard deviation) higher than for the surgical treatment. Compared with surgically castrated calves, those castrated by rubber ring gained less weight over the study period (on average 11.9 ± 5.1 kg less), a difference due in part to lower intake of calf starter (on average 1.8 ± 0.6 kg less). Calves in the rubber ring treatment spent less time lying down (on average 4.2 ± 1.2% fewer scans per day) and licked their lesions more frequently (on average 16.0 ± 3.3 more licks per day). We conclude that the rubber ring calves experienced more pain in the weeks following the procedure and thus recommend that surgical castration be favored for preweaning dairy calves.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".