Where to live? Landfast sea ice shapes emperor penguin habitat around Antarctica
Bibliographic record
Abstract
Predicting species survival in the face of climate change requires understanding the drivers that influence their distribution. Emperor penguins (Aptenodytes forsteri) incubate and rear chicks on landfast sea ice, whose extent, dynamics, and quality are expected to vary significantly due to climate change. Until recently, this species’ continent-wide observations were scarce, and knowledge on their distribution and habitat limited. Advances in satellite imagery now allow their observation and characterization of habitats across Antarctica at high resolution. Using circumpolar high-resolution satellite images, unique fast ice metrics, and geographic and biological factors, we identified diverse penguin habitats across the continent, with no significant difference between areas with penguins or not. There is a clear geographic partitioning of colonies with respect to their defining habitat characteristics, indicating possible behavioral plasticity among different metapopulations. This coincides with geographic structures found in previous genetic studies. Given projections of quasi-extinction for this species in 2100, this study provides essential information for conservation measures.
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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 | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".