Data from: Sexual dimorphism in epicuticular compounds despite similar sexual selection in sex role-reversed seed beetles
Bibliographic record
Abstract
Sexual selection imposed by mating preferences is often implicated in the evolution of both sexual dimorphism and divergence between species in signalling traits. Epicuticular compounds (ECs) are important signalling traits in insects and show extensive variability among and within taxa. Here, we investigate whether variation in the multivariate EC profiles of two sex role-reversed beetle species, Megabruchidius dorsalis and Megabruchidius tonkineus, predicts mate attractiveness and mating success in males and females. The two species had highly distinct EC profiles and both showed significant sexual dimorphism in ECs. Age and mating status in both species were also distinguishable by EC profile. Males and females of both species showed significant association between their EC profile and attractiveness, measured both as latency to mating and as success in mate-choice trials. Remarkably, the major multivariate vector describing attractiveness was correlated in both species, both sexes, and in both choice and no-choice experiments such that increased attractiveness was in all cases associated with a similar multivariate modification of EC composition. Furthermore, in both sexes this vector of attractiveness was associated with more male-like EC profiles, as well as those characterizing younger and nonvirgin individuals, which might reflect a general preference for individuals of high condition in both sexes. Despite significant sexual selection on EC composition, however, we found no support for the proposition that sexual selection is responsible for divergence in ECs between these species.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.074 | 0.022 |
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".