Pessimistic dairy calves are more vulnerable to pain-induced anhedonia
Bibliographic record
Abstract
Pain induces deficits in appreciation of rewards (i.e. anhedonia) and variation in response to pain may be partly explained by individual differences in general expectations (i.e. optimism). Dairy calves are routinely subjected to painful procedures such as hot-iron disbudding. We tested if female Holstein calves (n = 17) display signs of anhedonia (as evidenced by reduced consumption of a sweet solution) after hot-iron disbudding (performed under general and local anesthesia), and whether individual differences in optimism explain the variation in this response. Individual variation in optimism was measured using responses to two judgment bias tests (performed when calves were 25 d old), and anhedonia was measured by comparing consumption of a sweet solution before and after hot-iron disbudding. We found that intake of the sweet solution declined (by mean ± SD: 48.4 ± 44.3%) on the day after disbudding, and that more pessimistic calves were more affected. Sweet solution consumption did not return to baseline for the duration of the study (i.e. 5 days). Calves reduced their intake of a sweet solution after hot-iron disbudding, consistent with pain-induced anhedonia, and more pessimistic calves showed stronger evidence of anhedonia, suggesting that they were more affected by the procedure. However, our results cannot rule out the possibility that calf responses were driven by anorexia.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".