Individual vigilance profiles in flocks of House Sparrows (<i>Passer</i> <i>domesticus</i>)
Bibliographic record
Abstract
Individual vigilance against threats typically decreases with group size. However, group size often explains a small amount of variation in vigilance, suggesting that other factors such as individual differences might contribute. For instance, individuals could maintain different vigilance levels overall and also respond differently to variation in group size. We investigated individual variation in vigilance and its patterns of plasticity in flocks of House Sparrows (Passer domesticus (Linnaeus, 1758)). We carried out observations at one provisioned site and used multiple observations of the same individuals (n = 14) in flocks of different sizes over two consecutive months. The typical decline in vigilance with flock size occurred at the population level. Controlling for food density, flock size, time of year, and sex, we documented consistent individual differences in various measurements of vigilance. Plasticity of vigilance adjustments to variation in flock size occurred for the frequency of high vigilance postures. Male House Sparrows with larger bibs, which signal higher dominance status, tended to spend less time vigilant and obtained food at a higher rate, supporting a state-dependent explanation for the origin of individual vigilance profiles. Individual differences can contribute to explaining the large scatter in the relationship between vigilance and group size in many species.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".