Data from: Timing of egg-laying in relation to a female's social environment in European starlings
Bibliographic record
Abstract
It is widely assumed that female birds use non-photic supplemental cues, including social factors, to fine-tune timing of egg-laying to local conditions, but our knowledge of the nature of these social cues and how they operate remains limited. We analyzed the relationship between a female’s social environment (nearest neighbor distances, residency, female -and- network familiarity, synchrony) and variation in timing of egg-laying in European starlings (Sturnus vulgaris) using individual, residual laying date (controlling for annual variation) and temperature-independent residual laying date (accounting for the effect of ambient temperature on laying date). Female social environment varied systematically with overall spatial distribution of nest-boxes (linear vs clumped boxes) but this was not associated with spatial variation in laying date or temperature-independent residual laying date. We found no evidence for any relationships between individual variation in social environment and individual, residual laying date and only weak evidence for any association with individual, temperature-independent residual laying date. The latter was associated with a) nearest neighbor distances in the linear habitat, with females nesting closer to neighbors laying earlier than predicted by temperature, but not in the two clumped habitats, and b) neighbor familiarity: females with an intermediate number of returning females (3/8) laid closest to the predicted date. Finally, despite the fact that synchrony was not associated with other social environment metrics, females with lower laying synchrony among neighbors laid earlier than predicted by temperature. This suggests that some components of the female-female social environment could act as supplemental cues for timing of egg-laying.
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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 | 0.001 | 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) | 0.002 | 0.001 |
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".