Carotenoid availability affects the development of a colour-based mate preference and the sensory bias to which it is genetically linked
Bibliographic record
Abstract
Regardless of their origins, mate preferences should, in theory, be shaped by their benefits in a mating context. Here we show that the female preference for carotenoid colouration in guppies (Poecilia reticulata) exhibits a phenotypically plastic response to carotenoid availability, confirming a key prediction of sexual selection theory. Earlier work indicated that this mate preference is genetically linked to, and may be derived from, a sensory bias that occurs in both sexes: attraction to orange objects. The original function of this sensory bias is unknown, but it may help guppies find orange-coloured fruits in the rainforest streams of Trinidad. We show that the sensory bias also exhibits a phenotypically plastic response to carotenoid availability, but only in females. The sex-specificity of this reaction norm argues against the hypothesis that it evolved in a foraging context. We infer instead that the sensory bias has been modified as a correlated effect of selection on the mate preference. These results provide a new type of support for the hypothesis that mate preferences for sexual characters evolve in response to the benefits of mate choice--the alternatives being that such preferences evolve entirely in a non-mating context or in response to the costs of mating.
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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) | 0.002 | 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".