Influence of nearest neighbor distance and habitat structure on vigilance behavior
Bibliographic record
Abstract
One of the important antipredator benefits of group living for prey species is collective vigilance that enhances early predator detection. Within the group, individuals monitor the behavior of others to gauge the level of risk in the environment. The nearest-neighbor distance is important as the information travels quickly and easily from the nearest individuals. I examined the vigilance behavior of free-ranging chital deer (Axis axis, Gir Protected Area, India) in response to the group size, nearest neighbor distance, and habitat structure (open versus dense vegetation). The vigilance behavior showed a weak negative response to increases in group size. Overall, the vigilance levels were significantly higher for animals that had distant neighbors. There was a significant interaction effect of habitat structure and the nearest neighbor distance on vigilance levels of chitals. However, this effect was only significantly different for individuals living in dense vegetation. Chitals respond more strongly to conspecific vigilance from their nearest companion in the denser mixed forest than open acacia grasslands. The results indicate that nearest neighbor distance and habitat structure interact in determining the vigilance behavior of group living ungulates and transmission of information within a social group.
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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 | 0.000 |
| 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 | 0.000 |
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".