Data from: What makes a multimodal signal attractive? A preference function approach
Bibliographic record
Abstract
Courtship signals are often complex and include components within and across sensory modalities. Unfortunately, the evidence for how multimodal signals affect female preference functions is still rather limited. This is an important scientific gap because preference function shape can indicate which male traits are under the strongest selection. We modelled how preference function shape can be altered under 4 scenarios of varying signal content, including both redundant and non-redundant signals. The model was tested with the brown-headed cowbird (Molothrus ater); we manipulated male song attractiveness and visual display intensity, and assessed female preferences in an audiovisual playback study. We found that the intensity of a visual display can modify how attractive a song is for females. This indicates that the visual and acoustic male signal components are non-redundant and modulate each other. Our study shows a change in the direction of female preference functions for one signalling modality resulting from changes in the attractiveness of the other modality. Overall, our findings suggest that male signals in this species may not be under the typical directional selection documented in other species, but rather selection may favour males that possess a range of different signals that can be used strategically during different social contexts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.009 | 0.006 |
| 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 teacher head, 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".