Migration corridors of adult Golden Eagles originating in northwestern North America
Bibliographic record
Abstract
There has been increasing concern for Golden Eagle (Aquila chrysaetos) populations in North America due to current and future projections of mortality risk and habitat loss from anthropogenic sources. Identification of high-use movement corridors and bottlenecks for the migratory portion of the eagle population in western North America is an important first step to help habitat conservation and management efforts to reduce the risk of eagle mortality. We used dynamic Brownian Bridge movement models to estimate utilization distributions of adult eagles migrating across the western North America and identified high-use areas by calculating the overlap of individuals on population and regional levels. On a population level, the Rocky Mountain Front from east-central British Columbia to central Montana and southwestern Yukon encompassed the most used migration corridors with our study extent for both spring and fall. Regional analysis on a 100 x 200 km scale revealed additional moderate and high-level use corridors in the central British Columbia plateaus. Eagles were more dispersed in the spring until their routes converged in southern Alberta. High-use fall corridors extended farther south into central Wyoming. Knowledge of these high-use areas can aid in conservation and site planning to help maintain and enhance migratory Golden Eagle populations in western North America.
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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".