Neighbours' Breeding Success and the Sex Ratio of Their Offspring Affect the Mate Preferences of Female Zebra Finches
Bibliographic record
Abstract
Several hypotheses on divorce predict that monogamous pairs should split up more frequently after a breeding failure. Yet, deviations from the expected pattern "success-stay, failure-leave" have been reported in several species. One possible explanation for these deviations would be that individuals do not use only their own breeding performance (i.e., private information) but also that of others (i.e., public information) to decide whether or not to divorce. To test this hypothesis, we investigated the relative importance of private and public information for mate choice decisions in female zebra finches (Taeniopygia guttata).We manipulated the reproductive performance of breeding pairs and measured females' preferences for their mate and the neighbouring male first following pair formation and then seven weeks later when all females had laid eggs and the young were independent. Although all females reduced their preference for their mate after a breeding failure, the decrease was significant only when the neighbouring pair had reproduced successfully. Furthermore, there was no evidence that females biased the sex ratio of their offspring according to their mate's attractiveness. On the other hand, after reproduction, both successful and unsuccessful females increased their preferences for males who had produced a larger proportion of sons. Despite the fact that other mechanisms may have also contributed to our findings, we suggest that females changed their mate preferences based on the proportion of sons produced by successful males, because offspring sex ratio reflects the male's testosterone level at the moment of fertilization and hence is an indicator of his immune condition.
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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 | 0.000 | 0.001 |
| 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 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".