Bibliographic record
Abstract
Mutations arise spontaneously in all populations, and can severely diminish fitness. This mutation load is a key issue in evolutionary biology, affecting population persistence, the maintenance of genetic variation, and mating system evolution. The rate at which new mutations arise and their effects on fitness are generally treated as constant within a population, but theory suggests that variation in these parameters can have profound impacts. I explored the sex-specific effects of new mutations, and the role of condition in determining the mutation rate, using genotypes of Drosophila melanogaster loaded with spontaneous mutations. I found that the effect of mutations was more severe on male than on female fitness, pointing to a role for sexual selection in purging deleterious genetic variation. The expected consequence is that deleterious mutations will be eliminated at the expense of males, reducing the mutation load of sexual females, and thereby reducing the cost of sexual reproduction. I also found evidence that infection with a bacterial pathogen can heighten the degree of sex-specific selection. However, sex differences in selection could also reduce mean fitness if many alleles have sexually antagonistic effects. By comparing mutational and standing genetic variation, I tested for non-mutational variation in sexual fitness, which would be a signature of sexual antagonism. While there was some suggestion of sexual antagonism, deleterious mutations adequately explained levels of standing variation. Mutation load can also be affected if mutation rates depend on condition. I compared mutation rates across genotypes that varied in condition due to differences in genetic quality, and found that low condition caused elevated rates of mutational fitness decline. A genomic analysis revealed condition-dependent DNA repair pathway usage as the likely reason for this difference. Condition-dependent mutation is expected to reduce mean fitness in sexual populations, but may also increase the rate of extinction in asexuals.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".