Boldness affects foraging decisions in barnacle geese: an experimental approach
Bibliographic record
Abstract
Individuals foraging in groups constantly need to make decisions, such as when to leave a group, when to join a group, and when to move collectively to another feeding site. In recent years, it has become evident that personality may affect these foraging decisions, but studies where individuals are experimentally forced into different roles are still absent. Here, we forced individual barnacle geese, Branta leucopsis, differing in boldness scores, either in a joining or in a leaving role in a feeding context. We placed a food patch at the far end of a test arena and measured the arrival latency and number of visits of individuals to the patch either in the presence of a companion that was confined near the food patch (“joining context”) or in the presence of a companion that was confined away from the food patch (“leaving context”). We also ran trials without a companion (“nonsocial context”). Bolder individuals arrived more quickly than shyer individuals in the “leaving” context, but there was no effect of boldness in the “joining” context, suggesting that boldness differences are important in explaining variation in leaving behavior but not in joining behavior. The difference in arrival latency between the “joining” and non-social context increased with decreasing boldness score, suggesting that shyer individuals are more responsive to the presence of other individuals (i.e., social facilitation). These results indicate that individual differences in boldness play a role in patch choice decisions of group-living animals, such as when to leave a flock and when to join others at a patch.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".