The role of ecology, neutral processes and antagonistic coevolution in an apparent sexual arms race
Bibliographic record
Abstract
Some of the strongest examples of a sexual 'arms race' come from observations of correlated evolution in sexually antagonistic traits among populations. However, it remains unclear whether these cases truly represent sexually antagonistic coevolution; alternatively, ecological or neutral processes might also drive correlated evolution. To investigate these alternatives, we evaluated the contributions of intersex genetic correlations, ecological context, neutral genetic divergence and sexual coevolution in the correlated evolution of antagonistic traits among populations of Gerris incognitus water striders. We could not detect intersex genetic correlations for these sexually antagonistic traits. Ecological variation was related to population variation in the key female antagonistic trait (spine length, a defence against males), as well as body size. Nevertheless, population covariation between sexually antagonistic traits remained substantial and significant even after accounting for all of these processes. Our results therefore provide strong evidence for a contemporary sexual arms race.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".