LARGE-SCALE MOVEMENTS AND HABITAT CHARACTERISTICS OF KING EIDERS THROUGHOUT THE NONBREEDING PERIOD
Bibliographic record
Abstract
King Eiders (Somateriaspectabilis) breeding inwestern Canada and Alaska molt wing feathers andspend the winter in remote areas of the Bering Sea,precluding direct observation. To characterizetiming of migration and habitat used by King Eidersduring the nonbreeding period, we collectedlocation data for 60 individuals (27 femalesand 33 males) over three years from satellitetelemetry and utilized oceanographic informationobtained by remote sensing. Male King Eidersdispersed from breeding areas, arrived at wing moltsites, and dispersed from wing molt sites earlierthan females in all years. Males arriving earlierat wing molt sites molted flight feathers at higherlatitudes. Distributions of molt and winterlocations did not differ by sex or among years. Ofthe variables considered for analysis, distance toshore, water depth, and salinity appeared to bestdescribe King Eider habitat throughout thenonbreeding period. King Eiders were located closerto shore, in shallower water with lower salinitythan random locations. During the winter, lower iceconcentrations were also associated with King Eiderlocations. This study provides some of the firstlarge-scale descriptions of King Eider migrationand habitat outside the breeding season.
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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 | 0.000 | 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".