Diet of a breeding population of South Polar Skuas <i>(Stercorarius maccormicki)</i> of the Schirmacher Oasis, Central Dronning Maud Land, East Antarctica
Bibliographic record
Abstract
Abstract The first detailed study on the diet of a breeding population of South Polar Skuas (Stercorarius maccormicki) at Schirmacher Oasis is based on the collection and analysis of prey remains and pellets from the 2024/2025 breeding season and food samples from previous seasons near active skua nests (n=8) and old breeding territories (n=2). The diet composition of the skua population and its changes in the context of human activity were determined. The diet included five bird species, fish, squid, and food scraps and garbage from Antarctic stations and bases. The diet was dominated by Snow Petrels (Pagodroma nivea) , with subdominants being Antarctic Petrels (Thalassoica antarctica) and Adélie Penguins (Pygoscelis adeliae) . Native marine fish and squid were likely incidental dietary components, introduced into pellets along with the skuas’ prey. Human activities have influenced the diet of skuas on a population-wide scale by introducing imported food and garbage into their diet. Food waste was found in seven of eight surveyed breeding territories and in one of two old breeding territories. Diet composition and behaviour of skuas in areas of human activity in Antarctica can be used as an indicator of the quality of local human waste management, as well as an indicator of the health of the ecosystem.
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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 | 0.001 |
| 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".