Evolution of sexual dimorphism in phenotypic covariance structure in<i>Phymata</i>
Bibliographic record
Abstract
Sexual dimorphism is a consequence of both sex-specific selection and potential constraints imposed by a shared genetic architecture underlying sexually homologous traits. However, genetic architecture is expected to evolve to mitigate these constraints, allowing the sexes to approach their respective optimal mean phenotype. In addition, sex-specific selection is expected to generate sexual dimorphism of trait covariance structure (e.g., the phenotypic covariance matrix, P), but previous empirical work has not fully addressed this prediction. We compared patterns of phenotypic divergence, for three traits in seven taxa in the insect genus Phymata (Reduviidae), to ask whether sexual dimorphism in P is common and whether its magnitude relates to the extent of sexual dimorphism in trait means. We found that sexual dimorphism in both mean and covariance structure was pervasive but also that the multivariate distance between sex-specific means was correlated with sex differences in the leading eigenvector of P, while accounting for uncertainty in phylogenetic relationships. Collectively, our findings suggest that sexual dimorphism in covariance structure may be a common but underappreciated feature of dioecious populations.
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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 | 0.000 | 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".