The Effect of Social Environment on Male–Male Competition in Guppies (<i>Poecilia reticulata</i>)
Bibliographic record
Abstract
Abstract We examined male–male competition in guppies (Poecilia reticulata) to test for evidence of hierarchy formation and any subsequent effects on male mating success by comparing the interactions of pairs of males that were siblings and life‐long tank mates with those of unrelated pairs that had never met. These pairs of males were first observed in the absence of a female; then a female was added to gauge the effects of the initial male–male interactions on male sexual behaviour. The unfamiliar/unrelated pairs engaged in significantly more aggressive interactions such as physical contacts, nipping and chasing than the familiar/related pairs. Based on several previous studies, we suggest that familiarity played a greater role than relatedness in the differences in behaviour that we observed. Our results suggest that, in some circumstances, more aggressive males may have more mating opportunities than less aggressive males. Our results also indicate that males adjust their aggressive and courtship behaviours to the perceived intensity of competition for mates, based on the number of mature males in their rearing tanks. We suggest that male–male competition for mating opportunities may play a more important role in the guppy mating system than previously thought.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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".