Pigments, Patterns, and Fish Behavior
Bibliographic record
Abstract
Color patterns in fish are often multicomponent signals, composed of pigment-based and structural color patches that can be used to communicate within species, in both inter- and intrasexual interactions, and between species. In this review, we discuss some of the roles played by pigment-based elements of color pattern. We begin by discussing general forms of coloration, classifying them by appearance (e.g., cryptic vs. conspicuous) and apparent function (e.g., conspicuous coloration and mating displays, stripes and cooperation, and bars and aggression). We then briefly discuss the roles pigments play in the perception of these color patterns via their presence in the eye. In the last section, we look at the relative importance of carotenoid versus melanic coloration in situations where honest signals to potential rivals and potential mates might be required. In this survey, we have highlighted some recent research, especially studies that consider both the physiological and behavioral processes underlying the evolution and expression of pigment-based color patterns in fish. The nature of pigmented color patterns depends not just on the dynamics of pattern development and physiological regulation, but also on the behavioral roles played by these patterns, both now and in the past. As such, advances in particular fields of study on pigment patterns (physiology, developmental biology, behavioral ecology, evolutionary biology, etc.) will increasingly depend on insights from other fields.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".