THE POTENTIAL FOR SEXUALLY ANTAGONISTIC POLYMORPHISM IN DIFFERENT GENOME REGIONS
Bibliographic record
Abstract
Sex differences in the fitness effects of alleles at a single locus (intralocus sexual antagonism, or SA) have several evolutionary consequences. Among the consequences of SA, polymorphisms at genes partially linked to the sex-determining region of the sex chromosome pair potentially drive the evolution of suppressed recombination between the sex chromosomes. Understanding the conditions under which SA polymorphism can exist at such pseudo-autosomal (or PAR) loci should increase understanding of the evolution of recombination between sex chromosome pairs, and can help predict when we may expect potentially empirically detectable allele frequency differences between the sexes. Models so far published have concluded that PAR genes can maintain SA polymorphisms over a wider range of selection coefficients than autosomal ones, but have used restrictive assumptions. We expand the modeling of SA alleles at a single locus with the full range of degrees of linkage to the male-specific region, to include strong or weak selection and the possibility of different dominance coefficients in the two sexes. We confirm the previous major conclusion that SA polymorphisms are generally maintained in a larger region of parameter space if the locus is in the PAR than if it is autosomal.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".