Reduced diurnal activity and increased stopover duration by molting Swainson’s Thrushes
Bibliographic record
Abstract
Abstract Migration consists of a sequence of small- to large-scale flights often separated by stopovers for refueling. Tradeoffs between minimizing migration time (more flights, shorter stopovers) and maximizing energy gain (fewer flights, longer stopovers) will affect overall migration timing. For example, some individuals make long-term stopovers in high-quality habitat that maximize energy gain (e.g., molt-migration), but movement to those habitats likely costs time. We used radio telemetry and blood plasma metabolite levels to examine physiological and behavioral tradeoffs between molt-migrant (birds molting at the molt stopover; n = 59) and post-molt (birds that presumably completed their molt elsewhere; n = 19) migrant Swainson’s Thrushes (Catharus ustulatus) near Montreal, Canada. Molt-migration was a large time investment as the average stopover duration for molt-migrants was of 47 ± 9 days (~13% of the entire annual cycle), almost twice as long as previously assumed from banding records, and far longer than stopovers of post-molting individuals (7 ± 2 days). Daily mortality rate during the molt stopover was similar to the average annual daily mortality rate. Molt-migrants’ circadian rhythms closely matched light levels, whereas post-molting birds had irregular rhythms and averaged 1 hr greater activity per day than molt-migrants. Despite being less active, molt-migrants had similar refueling rates based on metabolite profiles. As compared with migrants that completed molt earlier, molt-migrants at this stopover site had slower subsequent migration rates. Thus, birds using long-term stopovers appeared to tradeoff energy (efficient refueling) for time (slower subsequent migration).
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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 | 0.001 | 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) | 0.002 | 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".