Phenotype-dependent social associations among male sexual rivals in a polygamous fish, the Trinidadian guppy (Poecilia reticulata)
Bibliographic record
Abstract
Recent theory predicts that males should choose the social context that maximizes their relative attractiveness to females while minimizing sperm competition risk.By preferentially associating with less attractive and less competitive sexual rivals, a male may increase his reproductive success.Using the Trinidadian guppy (Poecilia reticulata), I tested for non-random social associations among males in mixed-sex groups based on two phenotypic traits (body length, body colouration) that predict relative sexual attractiveness to females.In a dichotomous-choice test, focal males exhibited a significant preference for mixed-sex groups that included a less colourful and smaller male rival, thereby potentially increasing their relative attractiveness, as predicted.However, this preference was not expressed in nature.Males in mixed-sex shoals in a natural stream population in Trinidad were not assorted by either body length or colour, perhaps owing to constraints placed on preferred social associations by sexual conflict and the fission-fusion nature of guppy shoals.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".