Beauty in the eyes of the beholders: colour vision is tuned to mate preference in the Trinidadian guppy (<i>Poecilia reticulata</i>)
Bibliographic record
Abstract
A broad range of animals use visual signals to assess potential mates, and the theory of sensory exploitation suggests variation in visual systems drives mate preference variation due to sensory bias. Trinidadian guppies (Poecilia reticulata), a classic system for studies of the evolution of female mate choice, provide a unique opportunity to test this theory by looking for covariation in visual tuning, light environment and mate preferences. Female preference co-evolves with male coloration, such that guppy females from 'low-predation' environments have stronger preferences for males with more orange/red coloration than do females from 'high-predation' environments. Here, we show that colour vision also varies across populations, with 'low'-predation guppies investing more of their colour vision to detect red/orange coloration. In independently colonized watersheds, guppies expressed higher levels of both LWS-1 and LWS-3 (the most abundant LWS opsins) in 'low-predation' populations than 'high-predation' populations at a time that corresponds to differences in cone cell abundance. We also observed that the frequency of a coding polymorphism differed between high- and low-predation populations. Together, this shows that the variation underlying preference could be explained by simple changes in expression and coding of opsins, providing important candidate genes to investigate the genetic basis of female preference variation in this model system.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".