Prolonged spring migration in the Red-eyed Vireo (<i>Vireo olivaceus</i>)
Bibliographic record
Abstract
We used archival geolocators to track the migration of Red-eyed Vireos (Vireo olivaceus), abundant forest songbirds with significantly increasing breeding-population trends, to identify important stopover and wintering regions. All individuals from a single breeding site (n = 10) wintered in northwestern South America, an extensively forested region, and in spring used a consistent route, crossing the Gulf of Mexico from the Yucatan to Louisiana. Their spring migration rate (146 km day-1) was slower than that of most other songbirds tracked with geolocators from South America (>280 km day-1). Red-eyed Vireos had an unexpectedly prolonged stopover (mean ± SD =18.6 ± 4.9 days) in Colombia soon after the onset of spring migration, and we suggest that this area may provide important fruit resources for fueling subsequent, more rapid, migration. The total duration of spring migration averaged 45.9 ± 4.6 days, but individuals covered the journey of ∼6,600 km in an average of only 13 days of flight. Males arrived at the breeding site over a 15-day period, and arrival date was significantly correlated with departure date from the wintering site in South America (r = 0.81, P = 0.002), which is surprising, considering the prolonged and variable durations of stopovers en route. Even more intriguing, fall arrival date in South America was significantly correlated with individual departure in spring, which suggests that some birds are on year-round early-versus-late schedules.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".