Extra‐pair fertilization and effective population size in the song sparrow <i>Melospiza melodia</i>
Bibliographic record
Abstract
The concept of effective population size (N e ) is used widely by conservation and evolutionary biologists as an indicator of the genetic state of populations, but its precision and relation to the census population size is often uncertain. Extra‐pair fertilizations have the potential to bias estimates of N e when they affect the number of breeders or their estimated reproductive success tallied from social pedigrees. We tested if the occurrence of extra‐pair fertilizations influenced estimates of N e in a resident population of song sparrows Melospiza melodia using four years of detailed behavioural and genetic data. Estimates of N e based on social and genetic data were nearly identical and averaged c. 65% of the census population size over four years, despite that 28% of 471 independent young were sired outside of social pairs. Variance in male reproductive success also did not differ between estimates based on social and genetic data, indicating that extra‐pair mating had little effect on the distribution of reproductive success in our study population. Our results show that the genetic assignment will not always be necessary to estimate N e precisely.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".