Hatching order explains an extrapair chick advantage in western bluebirds
Bibliographic record
Abstract
Within-family comparisons of offspring growth rates have provided important tests of genetic benefits of extrapair mating for females. Here, we demonstrate that hatching order explains the growth advantage for extrapair young in western bluebirds (Sialia mexicana); extrapair nestlings are larger than within-pair nestlings in the same nest, but they also hatch earlier in the clutch, thus benefiting from hatching asynchrony. By controlling for hatch order and other nongenetic factors and comparing mixed-paternity broods with genetically monogamous broods, we show that the extrapair nestling growth advantage is not genetically based. We cannot rule out the possibility that females benefit from extrapair mating because genetic quality indicators may appear later in life and may be independent of hatch order, however, based on our results, we do not see evidence of genetic superiority of extrapair nestlings. Although findings similar to ours have been attributed to maternal effects, it is currently unclear whether overrepresentation of extrapair nestlings early in the laying and hatching sequence results from investment patterns of females, their social mates, or extrapair males. This study highlights the need to investigate the potentially complex interactions among all players, and how these may lead to higher performance of extrapair offspring compared with within-pair offspring within the same family.
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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".