Competing dwarf males: sexual selection in an orb‐weaving spider
Bibliographic record
Abstract
Hypotheses for the adaptive significance of extreme female-biased sexual size dimorphism (SSD) generally assume that in dimorphic species males rarely interfere with each other. Here we provide the first multivariate examination of sexual selection because of male-male competition over access to females in a species with 'dwarf' males, the orb-weaving spider Argiope aurantia. Male A. aurantia typically try to mate opportunistically during the female's final moult when she is defenceless. We show that, contrary to previous hypotheses, the local operational sex ratio (males per female on the web) is male-biased most of the season. Both interference and scramble competition occur during opportunistic mating, the former leading to significant selection for large male body size. Male condition and leg length had no effect on mating success independent of size. We discuss these findings in the context of the evolution of extreme female-biased SSD in this clade.
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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 | 0.000 |
| 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".