Spring migration routes and chronology of surf scoters (Melanitta perspicillata): a synthesis of Pacific coast studies
Bibliographic record
Abstract
Understanding interconnectivity among wintering, stopover, and breeding areas of migratory birds is pivotal to discerning how events occurring in each might have a cross-seasonal effect on another. Such information can guide the location and timing of conservation efforts. Thus, we examined spring migration routes, chronology, and stopover use of 85 surf scoters ( Melanitta perspicillata (L., 1758)) marked with satellite transmitters at four Pacific Flyway wintering sites: San Quintin Bay, Baja California; San Francisco Bay, California; Puget Sound, Washington; and Strait of Georgia, British Columbia. Eighty-three percent of marked scoters followed two main routes to the breeding area: a Southern Inland route involving staging in Puget Sound and Strait of Georgia and protracted inland migration, or a Northern Coastal route characterized by short movements along the Pacific coast of British Columbia and southeast Alaska with inland migration initiating from Lynn Canal and surrounding areas. Route choice was related to nesting site latitude in the Canadian Northern Boreal Forest. Data from birds tracked over 2 years indicated strong migration route fidelity, but altered chronology and stopover locations between years. Departure date varied by wintering site, but arrival and apparent settling dates were synchronous, suggesting individuals adjusted migration timing to meet an optimized reproductive schedule.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".