DOES SEA ICE CONSTRAIN THE BREEDING SCHEDULES OF HIGH ARCTIC NORTHERN FULMARS?
Bibliographic record
Abstract
The Northern Fulmar (Fulmarus glacialis) is a pelagic seabird that breeds across 25° of latitude, from the boreal to the high Arctic oceanographic zones. We examined the breeding schedule of fulmars in the remote Cape Vera colony in the Canadian high Arctic, a marine region covered by sea ice much of the year, to determine if the timing of breeding and colony attendance patterns of birds differed from the breeding phenology of fulmars in colonies farther south. Cape Vera fulmars arrived at the colony later in the year, spent less time at the colony before egg-laying, and took a significantly longer prelaying exodus from the colony compared to fulmars nesting in more southerly colonies. After egg-laying, however, patterns of colony attendance by fulmars in the high Arctic were similar to patterns for fulmars in southern colonies; this part of the fulmar breeding schedule may be inflexible. The differences in breeding schedules across the species' range might reflect behavioral adaptations by arctic-nesting birds to accommodate the physical and biological limitations imposed by extensive sea ice near arctic colonies, particularly early in the breeding season. Given that climate warming and corresponding reductions in sea ice are taking place in the Arctic, it remains to be determined whether fulmars in the high Arctic have the behavioral flexibility in their breeding phenology to compensate for rapidly occurring changes in their environment.
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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".