Influences of male and female phenotypes on male mate-choice copying in the Trinidadian guppy (Poecilia reticulata)
Bibliographic record
Abstract
Mate-choice copying in males is a form of social learning whereby an observer male modifies his inherent mating preference after observing a demonstrator male sexually interact with a female he did not initially prefer, and copies the mate preference of the demonstrator male. Little is known about such copying behaviour in males and how the phenotypes of males and(or) females interact to influence the likelihood of mate-choice copying and the strength of the copying response. Using the Trinidadian guppy (Poecilia reticulata), I investigated whether the relative sexual attractiveness of males influences the likelihood of mate-choice copying in males, and found that the highest rates of copying occurred when the demonstrator male was less sexually attractive than the observer male. Second, I tested whether the relative difference in the body size of paired females influenced the likelihood of male mate-choice copying, and did not find unequivocal evidence for such an effect.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".