Evolutionary Consequences of Male Driven Sexual Selection and Sex-Biased Fitness Modifications in<i>Drosophila melanogaster</i>and Members of the<i>simulans</i>Clade
Bibliographic record
Abstract
Males have evolved a variety of behavioral, morphological, and physiological traits to manipulate their mates in order to maximize their chances of success. These traits are bound to influence how females respond to male behaviors and influence the nature of sexual selection/conflict. A common consequence of aggressive male mating strategies in Drosophila melanogaster is the reduction of female lifespan. Our study shows that this is common across members of the simulans clade. Reduced life expectancy of females implies that female contribution to a population is less than that of males per generation. Fitness differences between the sexes in every generation will invariably affect overall population fitness. How natural selection responds to the female deaths and thereby the unequal fitness of the sexes has rarely been addressed. We shed light on this issue and provide evidence, which suggests that additional gains of fitness by males due to their longevity and continued mating may provide one explanation as to why the loss of female fitness may be "invisible" (effectively neutral) to natural selection. Male driven sexual selection and additional, transgenerational gains of male fitness can be an important force of evolutionary change and need to be tested with other organisms.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".