The Evolution of Sex Ratio Adjustment in the Presence of Sexually Antagonistic Selection
Bibliographic record
Abstract
Sex ratio adjustment (SRA) of broods has received widespread interest as a means for optimizing parental investment in offspring. Classical explanations for the evolution of SRA focus on improving offspring fitness in light of resource availability or mate attractiveness. Here, we use genetic models to demonstrate that SRA can evolve to alleviate sexual antagonism by improving the chance that the alleles of a sexually antagonistic trait are transmitted to the sex they benefit. In cases where the trait is autosomally inherited, this result is obtained regardless of whether SRA is based on the mother's or the father's genotype and irrespective of the recombination rate between the trait and SRA loci. SRA also evolves in this manner when the trait is sex-linked, provided that SRA decisions are based on the homogametic genotype (XX mothers or ZZ fathers). By contrast, when based on traits in the heterogametic sex, SRA promotes fixation of the allele that is detrimental to that sex, preventing the evolution of substantial levels of SRA. Our models indicate that the evolution of SRA in nature should be strongly influenced by the genetic architecture of the traits on which it is based and the form of selection affecting them.
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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 | 0.003 |
| 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 | 0.001 | 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".