Relationships among Breeding, Molting and Wintering Areas of Adult Female Barrow's Goldeneyes (<i>Bucephala islandica</i>) in Eastern North America
Bibliographic record
Abstract
While the breeding and wintering ranges of the eastern population of Barrow's Goldeneyes (Bucephala islandica) are generally described, molting locations and links among breeding, molting, and wintering areas are unclear, particularly for adult females. Incubating females from the same breeding location (n = 5) were equipped with satellite transmitters in June 2009. Four molting sites were identified over 2 years, spread broadly across Québec: an inlet in Ungava Bay 1,100 km from the breeding area, a lake 100 km south of Ungava Bay (880 km from breeding area), a lake near Hudson Bay (910 km from breeding area) and the mouth of the Rivière aux Outardes River in the St. Lawrence Estuary (165 km from breeding area). The distance between molting females averaged 755 km and two females molted in regions where males were known to molt. Of four birds with consecutive years of molt locations, three showed inter-annual fidelity to within 5 km of the previous molt sites and the fourth molted in sites that were 968 km apart. Females wintered in different locations within the St. Lawrence Estuary and moved widely throughout the area during winter. The south coast of the St. Lawrence Estuary was used during spring and fall staging, and the north coast during winter. There was not strong migratory connectivity among annual cycle stages in eastern adult female Barrow's Goldeneyes, indicating that they should be considered a single management unit that occurs over a broad range throughout the year.
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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 | 0.000 | 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".