Foraging ecology of Great Black-backed Gulls during brood-rearing in the Bay of Fundy, New Brunswick
Bibliographic record
Abstract
We studied nesting ecology of Great Black-backed Gulls (Larus marinus L., 1758) in the Bay of Fundy, New Brunswick, in 1988 and 1989. We documented diet, feeding rate, and meal size for chicks from hatching to fledging. In 1989, colonies consisted of about 350 nests on five islands. Brood size declined with chick age, and by the end of the first week of the nestling period, 11%, 22%, 31%, and 36% of nests consisted of broods of 0, 1, 2, and 3 chicks, respectively. Average meals size increased and feeding frequency declined slightly with chick age. We estimated that 619.6 kg (dry mass) of food was fed to chicks during the nestling period in 1989. The composition of the chicks' diet changed with age and was most varied early in the nestling period, when they were fed relatively equal proportions of major food types. Overall, Atlantic herring (Clupea harengus L., 1758) was the most important prey item and contributed 63% of the energy consumed by chicks during the nestling period. Northern krill (Meganyctiphanes norvegica (M. Sars, 1857); 11.9%), lumpfish (Cyclopterus lumpus L., 1758; 10.4%), and waste (fisheries and domestic; 4.7%) were also important foods. Gull chicks and Common Eider (Somateria mollissima (L., 1758)) ducklings made up 1.9% and 0.8%, respectively, of the chicks' energy budget. We conclude that the primary factor effecting productivity of the Great Black-backed Gull was food availability, and the amount of food available varied little over the nesting period in 1989.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".