Males from populations with higher competitive mating success produce sons with lower fitness
Bibliographic record
Abstract
Female mate choice can result in direct benefits to the female or indirect benefits through her offspring. Females can increase their fitness by mating with males whose genes encode increased survivorship and reproductive output. Alternatively, male investment in enhanced mating success may come at the cost of reduced investment in offspring fitness. Here, we measure male mating success in a mating arena that allows for male-male, male-female and female-female interactions in Drosophila melanogaster. We then use isofemale line population measurements to correlate male mating success with sperm competitive ability, the number of offspring produced and the indirect benefits of the number of offspring produced by daughters and sons. We find that males from populations that gain more copulations do not increase female fitness through increased offspring production, nor do these males fare better in sperm competition. Instead, we find that these populations have a reduced reproductive output of sons, indicating a potential reproductive trade-off between male mating success and offspring quality.
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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) | 0.001 | 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 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".