IDENTIFICATION OF GENETICALLY LINKED FEMALE PREFERENCE AND MALE TRAIT
Bibliographic record
Abstract
Genetic variation in male traits and the female preferences for those traits allows for the evolution of sexual behavior. Trait-preference combinations are thought to improve the effectiveness of runaway sexual selection within a species, and are considered necessary for the induction of divergence between species. Novel traits, or variants of existing traits, and their associated preferences in the opposite sex are more likely to be maintained if they are genetically linked in proximity on a chromosome (the genetic coupling hypothesis), yet there is little empirical evidence that this genetic linkage occurs. Here we show for the first time that natural genetic variation at a single-linked region can induce both species-specific female choosiness and the male trait they are discriminating against. We found this effect in two separate regions of the genome, demonstrating that this linkage may be common. In contrast, female choosiness and male unattractiveness could not be alleviated by a single region. The close linkage of these loci and the strength of their effect provide an evolutionary means by which this preference-trait combination could arise and be maintained, thus enabling a more rapid route for runaway sexual selection, and providing empirical evidence supporting the genetic coupling hypothesis.
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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".