Conditioned place aversion of caustic paste and hot-iron disbudding in dairy calves
Bibliographic record
Abstract
Cauterization by hot iron and application of caustic paste are 2 common methods of disbudding calves. In this study, we compared the affective experience of these 2 procedures on young dairy calves using conditioned place aversion. Male dairy calves (n = 14; 7 ± 2 d old) were disbudded by both thermal and chemical methods (1 horn bud at a time, 48 h apart). Calves received treatments in pens made visually distinct with either red squares or blue triangles on the walls. Calves were restricted to these treatment pens for 6 h following disbudding. For all treatments, calves received a sedative (xylazine, 0.2 mg/kg), local anesthetic (lidocaine, 5 mL), and analgesic (meloxicam, 0.5 mg/kg). Calves were then tested for conditioned place aversion at 48, 72, and 96 h after their last treatment. During tests, calves were placed in a neutral pen connected to both treatment pens where they had previously been disbudded. Time spent in each treatment pen was recorded until calves chose to lie down for 1 min (latency to lie down: 31.0 ± 8.6 min). During the first test (48 h after last disbudding), calves spent more time in the pen associated with hot-iron disbudding compared with what would be expected by chance (intercept: 73.5%, 95% CI: 56.5, 90.5) and fewer calves lay down in the caustic paste pen than in the hot-iron pen (3 vs. 10 lying events). No evidence of preference for the hot-iron pen was found in the following test sessions (72 and 96 h since last disbudding). These results suggest that calves initially remember caustic paste disbudding as a more negative experience than hot-iron disbudding, even with the use of sedation, local anesthesia, and analgesia.
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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".