Differential rates of offspring provisioning in Gould’s petrels: are better feeders better breeders?
Bibliographic record
Abstract
Procellariiformes (albatrosses and petrels) must accumulate substantial energy reserves to sustain them while incubating their single egg. They then produce a chick that is often more than 130% of their own body mass. Thus, despite the variable nature of resource availability in the marine environment, successful reproduction requires a considerable increase in foraging rates. Birds that are better foragers are, therefore, likely to be better parents. As surrogates of foraging ability, we assessed two parental traits that are separated temporally over the breeding season, body condition during incubation and provisioning performance, in Gould’s petrel (Pterodroma leucoptera). Although parental condition did not influence hatching success, we found significant positive correlations between the average body condition of a breeding pair and both the growth rate of chicks (g day–1) and the body condition of chicks at peak mass. Provisioning rate also correlated positively with chick condition. Chick condition was positively correlated with haemoglobin concentration [Hb] at peak mass, which was positively correlated with [Hb] at fledging. Because the probability of survival after fledging may be influenced by chick body condition and [Hb], the ability of parents to acquire additional resources for breeding is likely to be an important determinant of reproductive success.
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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 | 0.000 |
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".