Hatch timing and maternal bill colouration are associated with chick growth in a mutually ornamented seabird
Bibliographic record
Abstract
In species with obligate bi-parental care, investment by both parents in a current reproductive bout is critical to offspring growth and survival. The degree to which an individual can invest in their offspring relies on their quality as a parent. Parental quality can be communicated between individuals in a mated pair via ornamental features, as they may honestly reflect aspects of direct or indirect offspring contribution. In this study, we investigated whether the red-orange bill colouration in Atlantic puffins Fratercula arctica reflects two proxies of parental quality: hatch date and offspring growth. No aspect of paternal colouration predicted hatch date, but several metrics of maternal colouration predicted offspring peak mass and normalized wing growth. We also explored whether hatch date influenced patterns of chick growth and found that timing (early hatch vs. late hatch) but not synchrony with food availability significantly predicted mass and skeletal growth. Specifically, early hatching chicks achieved higher peak masses but exhibited reduced wing growth, potentially reflecting alternative strategies between investing primarily in weight gain or structural development. Together, these results highlight chick growth as a complex metric of parental quality, associated with both phenology and parental phenotype.
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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".