Cascading effects of pre-adult survival on sexual selection
Bibliographic record
Abstract
Sexual selection influences broad-scale patterns of biodiversity. While a large body of research has investigated the effect of mate competition on sexual selection, less work has examined how pre-adult life history influences sexual selection. We used a mathematical framework to explore the influence of pre-adult survival on sexual selection. Our model suggests that pre-adult male mortality will affect the strength of sexual selection when a fixed number of adult males have an advantageous mate-acquisition trait. When a fixed number of males have an advantageous mate-acquisition trait, sexual selection is expected to increase when pre-adult mortality is relatively low. By contrast, if a fixed proportion (rather than number) of adult males have a mate-acquisition trait, pre-adult male mortality is not expected to affect the strength of sexual selection. Further, if the advantageous mating trait affects pre-adult survival, natural and sexual selection can interact to influence the overall selection on the mating trait. Given that pre-adult mortality is often shaped by natural selection, our results highlight conditions under which natural selection can have cascading effects on sexual selection.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".