Diet dichotomy between two migrant seabirds breeding near a high Arctic polynya
Bibliographic record
Abstract
High Arctic polynyas are predictable areas of open water, which offer long-distance migrant seabirds a reliable source of food during a period when they have to replenish and accumulate energy for reproduction. Investigating the interaction between species nesting sympatrically in the vicinity of polynyas should provide insights into the role that such oceanographic features play for pre-breeding seabirds. We used stable isotopes (δ13 C and δ15 N) to compare the diet of two ground-nesting seabirds, Sabine’s gull (Xema sabini) and Arctic tern (Sterna paradisaea), nesting on an island adjacent to a recurring polynya in the Canadian high Arctic in 2008 and 2009. We show that, unlike Arctic terns, the diet of Sabine’s gulls appears to include a non-negligible amount of terrestrially derived prey during early incubation, and that overall both species segregate their dietary niche during pre-laying and early incubation
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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; both teacher heads agree on what is shown here.
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".