SEXUAL SELECTION AND THE EVOLUTION OF GENITAL SHAPE AND COMPLEXITY IN WATER STRIDERS
Bibliographic record
Abstract
Animal genitalia show two striking but incompletely understood evolutionary trends: a great evolutionary divergence in the shape of genitalic structures, and characteristic structural complexity. Both features are thought to result from sexual selection, but explicit comparative tests are hampered by the fact that it is difficult to quantify both morphological complexity and divergence in shape. We undertake a comparative study of multiple nongenitalic and male genital traits in a clade of 15 water strider species to quantify complexity and shape divergence. We show that genital structures are more complex and their shape more divergent among species than nongenital traits. Further, intromittent genital traits are more complex and have evolved more divergently than nonintromittent genital traits. More importantly, shape and complexity of nonintromittent genital traits show correlated evolution with indices of premating sexual selection and intromittent genital traits with postmating sexual selection, suggesting that the evolution of different components of genital morphology are shaped independently by distinct forms of sexual selection. Our quantitative results provide direct comparative support for the hypothesis that sexual selection is associated with morphological complexity in genitalic traits and highlight the importance of quantifying morphological shape and complexity, rather than size in studies of genital evolution.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".