Catching the red eye: field evidence that artificial prey with red eye-like markings are preferentially avoided by avian predators
Bibliographic record
Abstract
Abstract Calyptrate muscoids (Diptera: Schizophora) are globally distributed flies and among the most maneuverable of flying insects. A salient feature of many calyptrate species is their large red eyes. Given their abundance and evasiveness, it has been postulated that birds might learn to associate the red eye trait with difficulty of capture, and subsequently avoid this prey type. This hypothesis is strengthened by the observation that many arthropods, from spiders to weevils, appear to have evolved a resemblance to calyptrates, including their prominent red eyes. To test the hypothesis directly we pinned 1000 artificial beetles with grey and red eyes onto trees over three separate transects and inspected them 26 days later. As predicted, there was over twice the predation on grey-eyed beetles than red-eyed beetles. The implications of this result are discussed, including how one could quantify the ecological and phylogenetic association between a signaller’s red eyes and its evasiveness.
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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) | 0.003 | 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".