Data from: Multi-functional crest display in hoopoes Upupa epops
Bibliographic record
Abstract
Animals can engage in visual displays, which may target conspecifics, heterospecifics or both. Here we studied the function of the flamboyant crest-raising display of hoopoes (Upupa epops) in experiments performed with males in captivity. Males were exposed to sounds of a conspecific (male hoopoe song), a potential predator (human voice), and two controls (the song of a blackbird, Turdus merula, and background noise). These stimuli were presented to males in the presence and absence of females. Males raised the crest with a significantly higher probability when confronted with stimuli indicating potential threats (rival mate or predator) than with controls. The crest display was frequent when confronted with both kinds of threats independently of the presence of a female, suggesting that it was directed to the predator and the rival male. The probability of raising the crest was not related to body condition, and there was a marginally but not significant negative relationship between probability of raising the crest and the number of black spots on the crest feathers, which may suggest that crest display could be informing about male quality. Therefore, male hoopoes display the crest in a heterospecific context in response to detection of potential threats, which could be a deceptive or pursuit-deterrent signal. The results also support a role of the crest in sexual selection, suggesting that crest display in male hoopoes may serve multiple functions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.007 |
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".