Does cognitive performance predict contest outcome in pigs?
Bibliographic record
Abstract
Losing aggressive contests may impact survival, reproductive success and animal welfare . Previous experience plays an important role in shaping contest behaviour , but less is known about how individual variation in learning abilities influences contest dynamics and resource-holding potential. Here, we investigated whether learning performance (acquisition learning and reversal learning) in domestic pigs , Sus scrofa , predicts the outcome of a contest against an unfamiliar opponent. While acquisition learning speed did not predict contest outcome, pigs that successfully learned the reversal were more likely to win the contest than pigs that failed to learn the reversal. As expected, weight difference between opponents was also an important factor in predicting contest outcome. Our results suggest that cognitive flexibility may confer an advantage in contests, unless pigs already have a substantial weight advantage over their opponent. These findings advance our understanding of the role of cognitive processes in animal contests and suggest that promoting cognitive flexibility may reduce the potential welfare impacts arising from stressful social defeat. Further research is required to determine whether cognitive flexibility influences assessment strategy and allows pigs to resolve contests with fewer costs.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 teacher head, 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".