Survival analysis of Little Penguin<i>Eudyptula minor</i>chicks on Motuara Island, New Zealand
Bibliographic record
Abstract
Chick survival of Little PenguinsEudyptula minorwas studied on predator‐free Motuara Island, Cook Strait, New Zealand (41d̀05'S, 174d̀15'E), in 1995 and 1996. We used the Kaplan‐Meier estimator and robust Cox regression to estimate chick survival rate (pL se) at 0.325 pL 0.044, leading to an estimated survival from laying to fledging of 0.13 or a reproductive output of 0.26 chicks per pair and breeding attempt. Starvation posed the greatest mortality risk, followed by unknown factors and rain. Risk of death due to rain was restricted to the guard stage, whereas starvation occurred throughout the nesting period, though with a peak in the early guard stage. Significant seasonal differences in survival rate were detected in both years, but with reversed trends, survival decreasing with the season in 1995 and increasing in 1996. Failure of adults to relieve their partner on the nest after chicks hatched accounted for 16% mortality or 34% of all chick deaths. Differences in chick survival rate between nest types were significant in 1995, a year with high rainfall, but not in 1996. Nests in the base of hollow trees had the highest chick survival rate. Of chicks in open nests ‐ a nest type that is unusual for this species ‐ 5.4% fledged. Our results suggest that on Motuara Island good breeding sites are scarce and that the food supply has been poor during the years of this study.
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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".