Plumage brightness predicts non‐breeding season territory quality in a long‐distance migratory songbird, the American redstart <i>Setophaga ruticilla</i>
Bibliographic record
Abstract
Many species of birds exhibit brilliant ornamental plumage, yet most research on the function and evolution of plumage has been confined to the breeding season. In the American redstart Setophaga ruticilla , a long‐distance Neotropical‐Nearctic migratory bird, the acquisition of a winter territory in high‐quality habitat advances spring departure and subsequent arrival on breeding areas, and increases reproductive success and annual survival. Here, we show that males holding winter territories in high‐quality, black mangrove habitats in Jamaica have brighter yellow‐orange tail feathers than males occupying territories in poor‐quality second‐growth scrub habitats. Moreover, males arriving on the breeding grounds from higher‐quality winter habitats (inferred by stable‐carbon isotopes) also had brighter tail feathers. Because behavioral dominance plays an important role in the acquisition of winter territories, plumage brightness may also be related to fighting ability and the acquisition and maintenance of territories in high‐quality habitat. These results highlight the need for further research on the relationships between plumage coloration, behavior, and the ecology of over‐wintering migratory birds.
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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) | 0.002 | 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".