The effects of wind and fuel stores on stopover departure behavior across a migratory barrier
Bibliographic record
Abstract
During annual migrations between breeding and nonbreeding grounds, billions of land birds encounter migratory barriers en route . Although birds are thought to be more selective (i.e., cross under favorable wind conditions) and spend more time refueling at stopover sites when confronted with these barriers, there is no direct evidence to support these hypotheses. Using 2 automated radio-telemetry arrays at stopover sites situated before (south of) and after (north of) a large ecological barrier (Lake Erie), we tracked departure decisions of American redstarts Setophaga ruticilla and yellow-rumped (myrtle) warblers Setophaga coronata coronata during spring migration. We found evidence that condition, age, and tailwind assistance were all positively correlated with the likelihood of departure. Interestingly, these patterns did not differ between species, with presumably differing migratory tactics, nor across sites, suggesting that during spring migration, migratory songbirds may follow general rules for departure from stopover sites, despite varying ecological and life-history contexts.
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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 | 0.002 |
| 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".