Sexual Selection and the Random Union of Gametes: Testing for a Correlation in Fitness between Mates in<i>Drosophila melanogaster</i>
Bibliographic record
Abstract
Both males and females vary in fitness. While high-fitness males typically have greater siring success, it is not clear whether these males sire an equal fraction of offspring from all females or a disproportionately large fraction with high-fitness females. The latter nonrandom reproductive pattern can arise as the result of sexual selection and creates a positive correlation in fitness between mates. Such a correlation, if it reflects a positive genetic correlation between mates with respect to fitness, increases the efficiency of selection, reducing mutation load and speeding adaptation. While there is evidence from many taxa that assortative mating for fitness may occur, these studies typically focus on observed matings rather than realized reproductive output. Here, we examine assortative mating for fitness in Drosophila melanogaster, first in the context of virgin matings and then using a measure of realized reproduction that incorporates remating and postcopulatory processes. We find evidence for positive assortative mating among virgins but no evidence of assortative mating using the more complete measure of reproduction.
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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 | 0.003 | 0.005 |
| 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 | 0.000 | 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".