Atlantic Puffin (<i>Fratercula arctica</i>) chick diet and reproductive performance at colonies with high and low capelin (<i>Mallotus villosus</i>) abundance
Bibliographic record
Abstract
We compared nestling diet and growth, breeding phenology, breeding success, and adult mass of Atlantic Puffins (Fratercula arctica) between two seabird colonies adjacent to ocean habitat with presumed high and low capelin (Mallotus villosus) abundance in 19961998. We hypothesized that puffins at their colony at Gannet Islands, Labrador, where capelin were scarce, would exhibit lower reproductive performance than at Gull Island, Witless Bay, where capelin were abundant. Historically, capelin comprised approximately 60%95% of the chick diet biomass at both colonies. In the late 1990s, puffin chicks at the Gannet Islands received 3%24% capelin (by mass), which was 39%97% less than was received at Gull Island. Postlarval sandlance (Ammodytes sp.) comprised up to 49% (by mass) of the chick diet at the Gannet Islands. Hatching success and fledge success estimates at the Gannet Islands in 19971998 were statistically similar to those at Gull Island in 1998. Fledge mass (expressed as percentage of adult mass) was similar between Gannet Islands (69%) and Gull Island (68%). The high interyear variability in chick diet at both colonies and the low variation in breeding performance during our study suggest that Atlantic Puffins in Labrador are resilient to large-scale prey-base changes.
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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 | 0.000 |
| 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".