Sperm-expenditure strategies: the role of mating order, sperm precedence, and non-optimal behavior
Bibliographic record
Abstract
We developed a model to examine the amount of sperm that males should transfer to females under different conditions of sperm precedence. Following a previous model (Parker's), we assume the existence of nonrandom mating roles in which there are males that always mate first and others that always mate second. However, we alter Parker's model by introducing the possibility that males are non-optimal in their sperm allocation (because males make mistakes or are interrupted, or because of phenotypic variation among males). We predicted that when males behave optimally, their sperm expenditures will be equal for most levels of sperm precedence, regardless of whether they mate first or second. However, when the possibility that males behave non-optimally is included, we predicted (i) a positive correlation between the allocations of first and second males when there is second-male precedence, (ii) a negative correlation when there is first-male precedence, and (iii) no correlation when there is no precedence. We discuss these and other predictions and provide supporting evidence from the literature.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".