Are virgin male lepidopterans more successful in mate acquisition than previously mated individuals? A study of the European corn borer, <i>Ostrinia nubilalis</i> (Lepidoptera: Pyralidae)
Bibliographic record
Abstract
Male phenotypic quality may significantly influence female reproductive success. Depletion of sperm and accessory-gland secretions with successive matings represents a reduction in male phenotypic quality and is known to decrease female reproductive output in several lepidopteran species, including the European corn borer (ECB), Ostrinia nubilalis. We therefore tested the hypothesis that female ECBs, given the simultaneous choice of an experienced male and a virgin male, preferentially mate with the virgin. However, contrary to prediction, females mated significantly more often with experienced males. Experienced males were significantly lighter than their virgin counterparts, the result of producing three spermatophores that were transferred during previous matings. However, differences in body mass or wing-loading did not appear to play an important role, for within either the experienced or virgin classes, heavier males obtained more matings than lighter ones. Why would females prefer to mate with sexually experienced males? Females may not be exercising any precopulatory choice, and the greater mating success of previously mated males may be related to previous experience. Behavioral observations, however, suggest that female choice occurred. In the process of selecting experienced males, the number of consecutive matings was correlated with low fluctuating asymmetry of the forewing (R-L). This suggests that males who acquired 3 consecutive matings were of above-average quality and were actively selected by females.
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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 | 0.000 |
| 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 | 0.000 |
| 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".