Reviewing guppy color vision: integrating the molecular and physiological variation in visual tuning of a classic system for sensory drive
Bibliographic record
Abstract
Sensory drive predicts coevolution of mate choice signals with the sensory systems detecting those signals. Guppies are a classic model for sensory drive as mate preferences based on coloration differ across individuals and populations. A large body of work has identified variation in color vision, yet we lack a direct tie between how such variation in color vision influences variation in color preference. Here we bring together studies that have investigated guppy vision over the past 40 years to: (1) highlight our current understanding of where variation occurs in the guppy color vision pathway and (2) suggest future avenues of research into sources of visual system variation that could influence guppy color preference. This will allow researchers to design careful studies that couple measures of color preference with measures of visual system variation from the same individual or population. Such studies will finally provide important answers as to what sets the direction and speed of mate preference evolution via sensory drive.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".