Complex social housing reduces food neophobia in dairy calves
Bibliographic record
Abstract
Animals are often reluctant to consume novel feeds. Research suggests that social housing can reduce fearfulness in animals. The aim of this study was to test the prediction that social housing reduces food neophobia in dairy calves. Beginning immediately at birth, Holstein bull calves were either reared individually (n=18) or in a complex social group with other calves and cows (n=18). In food neophobia tests, calves were exposed to 2 identical buckets, one empty and the other filled with a novel food (chopped hay in trial 1 and chopped carrots in trial 2). Calves were tested for 30 min/d on 3 consecutive days starting at 70 d of age. Regardless of the type of food, socially housed calves consumed more of the novel feed compared with individually housed calves. In trial 1, intake of hay as fed averaged 35 ± 6 versus 18 ± 6 g/d for socially versus individually housed calves. In trial 2, intake of chopped carrots as fed averaged 27 ± 6 versus 6 ± 6 g/d for socially versus individually housed calves, respectively. Social rearing decreased the latency to eat the novel feed. Calves housed in a complex social group began eating the hay after 1:23 ± 1:13 versus 3:58 ± 1:10 min:s for individually housed calves. Latency to begin eating the chopped carrots averaged 3:09 ± 1:17 versus 6:38 ± 1:13 min:s for socially versus individually housed calves. Treatment had no effect on time spent eating, latency to approach the food bucket or the empty bucket in either trial, or on time spent manipulating the empty bucket. These results indicate that housing dairy calves in a complex social group reduces food neophobia. More generally, this study contributes to a series of studies showing that calves raised in more complex social environments may be better able to transition to other changes in their environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".