Bibliographic record
Abstract
In general, females are less ornamented than males and until recently female ornaments have been regarded as non-adaptive correlated effects of selection on males. This view is challenged and the alternative hypothesis that females' ornaments have evolved independently of male showiness, by intersexual selection for example, is supported. I tested these hypotheses experimentally using threespine sticklebacks (Gasterosteus aculeatus) from a population in which both sexes have red pelvic spines. Two females differing in red spine colour extravagance were presented simultaneously to a male under white and green light, and the male's courtship activity towards each female was quantified. Green light prevented the use of red cues by sticklebacks. The results show that red colour on the pelvic spines of female sticklebacks has value as a signal to males in this population, and males actually courted females with drab pelvic spines more than females whose pelvic spines had a redder hue, but only when illuminated by white light. The interpretation that best accounts for this result is that spine colour has a strong function in malemale aggressive interactions. This interpretation favours the hypothesis of non-adaptive correlation that has been proposed to explain the evolution of red spines in female sticklebacks.
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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 | 0.001 | 0.000 |
| 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".