An Experimental Analysis of Spatial Position Effects on Foraging and Vigilance in Brown‐Headed Cowbird flocks
Bibliographic record
Abstract
Abstract Several observational studies have found that the costs and benefits of social foraging vary as a function of spatial position in the group. However, it is difficult to make mechanistic inferences because several confounding factors, such as food deprivation levels, food availability, neighbor distance, and group size can mask or amplify spatial position effects. We attempted to address experimentally the effect of spatial position on foraging and vigilance in a group, controlling for many confounding factors. We used enclosures that restricted physical but not visual interactions between brown‐headed cowbirds and manipulated spatial position, flock size, and neighbor distance. Pecking rate (number of pecks per trial duration) was not related with position, but instantaneous pecking rate (number of pecks per foraging bout duration) was higher at the edge. The proportion of time spent head‐up (scanning and food‐handling) was also higher at the edge. For pecking rate and proportion of time spent scanning, changes in neighbor distance influenced the behavior of edge birds to a lesser extent than central birds. These results suggest that cowbirds at the edge perceived greater predation risk and that during the limited foraging time available, edge birds tried to compensate by foraging at a faster rate.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".