Eavesdropping of an African ground squirrel on the heterospecific alarm calls of a noisy ground‐nesting bird
Bibliographic record
Abstract
Abstract Animals gather information about their environment from a variety of sources to enable adaptive decision‐making behaviour. Eavesdropping on heterospecific alarm calls enhances predator avoidance, reduces time spent vigilant and allows for more time on daily activities such as foraging. If the information is relevant and reliable, individuals that respond to heterospecific signals may benefit from a wider range of information at a low marginal cost. The Cape ground squirrel (Xerus inauris) and crowned lapwing (Vanellus chilensis) are ground‐dwelling species that are taxonomically distant but share similar predators, habitat and anti‐predatory behaviours. We used playback experiments of the alarm calls produced by conspecifics and lapwings to investigate the vigilance responses of adult female Cape ground squirrels. Squirrels responded with greater vigilance to both squirrel and lapwing alarm calls, and no changes of vigilance levels were observed in response to a control sound. However, contrary to our predictions, changes in vigilance and time to relax did not differ between conspecific versus heterospecific playbacks. The results from our study suggest that squirrels perceive lapwing alarm calls as relevant and reliable information and that responding to it could increase their survival.
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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 | 0.000 | 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".