Correlated paternity measures mate monopolization and scales with the magnitude of sexual selection
Bibliographic record
Abstract
Indirect measures of sexual selection have been criticized because they can overestimate the magnitude of selection. In particular, they do not account for the degree to which mating opportunities can be monopolized by individuals of the sex that compete for mates. We introduce a measure of mate monopolization (m) based on the magnitude of correlated paternity and evaluate its ability to track changes in the magnitude of sexual selection. Simulation models were used to compare how well m tracked changes in the selection differential (s) for a trait regulating mating success. We further evaluated the association between m and s using ten replicate mating arrays of Sagittaria latifolia in which plants with contrasting alleles at microsatellite loci competed for siring opportunities. The computer models and mating arrays both demonstrated a positive linear association between m and s, supporting the utility of m as an index of sexual selection. Commonly used measures of sexual selection are not easily applied to organisms, such as the flowering plants, for which mating events are difficult to observe. The measure of mate monopolization introduced here could prove to be a useful addition to studies of sexual selection in these organisms.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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".