Exploring dairy heifers' consistency in social motivation in the absence or presence of conspecifics
Bibliographic record
Abstract
We examined the consistency of heifers’ (n=36) sociability in the absence and presence of conspecifics. We applied standard animal personality tests to measure social motivation during social isolation. Additionally, we developed two novel test paradigms designed to quantify heifers’ willingness to trade off access to conspecifics in exchange for feed, thus measuring social motivation within a social context. In our distribution test, groups of three dairy heifers (n=12) could freely move between two feed troughs where grain was provided at two rates, with one providing twice as much feed as the other. Time feeding alone in the distribution test varied among heifers from 0 to 56.6 % of the time; this variation was weakly associated with differences in sociability as assessed by the time animals took to return to peers following social isolation, but not with heifers’ willingness to leave peers to access grain when tested in an alternative social-feed trade-off test. Our findings suggest that different measures of social motivation are not necessarily consistent, challenging the assumption that sociability is a stable personality trait in cattle. Instead, we propose to regard sociability as a ‘behavioural consequence’ resulting from the combined effects of internal characteristics (e.g., other personality traits such as fearfulness) and external factors (e.g., testing environment) at the time of evaluation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".