A Puzzling Migratory Detour: Are Fueling Conditions in Alaska Driving the Movement of Juvenile Sharp-Tailed Sandpipers?
Bibliographic record
Abstract
Making a detour can be advantageous to a migrating bird if fuel-deposition rates at stopover sites along the detour are considerably higher than at stopover sites along a more direct route. One example of an extensive migratory detour is that of the Sharp-tailed Sandpiper (Calidris acuminata), of which large numbers of juveniles are found during fall migration in western Alaska. These birds take a detour of 1500–3400 km from the most direct route between their natal range in northeastern Siberia and nonbreeding areas in Australia. We studied the autumnal fueling rates and fuel loads of 357 Sharp-tailed Sandpipers captured in western Alaska. In early September the birds increased in mass at a rate of only 0.5% of lean body mass day-1. Later in September, the rate of mass increase was about 6% of lean body mass day-1, among the highest values found among similar-sized shorebirds around the world. Some individuals more than doubled their body mass because of fuel deposition, allowing nonstop flight of between 7100 and 9800 km, presumably including a trans-oceanic flight to the southern hemisphere. Our observations indicated that predator attacks were rare in our study area, adding another potential benefit of the detour. We conclude that the most likely reason for the Alaskan detour is that it allows juvenile Sharp-tailed Sandpipers to put on large fuel stores at exceptionally high rates.
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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 | 0.000 | 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".