Data from: Does white tail patch size indicate quality in male Cerulean Warblers (Setophaga cerulea)
Bibliographic record
Abstract
Within species of birds, variation in plumage may allow potential mates or competitive rivals to quickly assess the quality of an individual. Little is known about the role of white tail feather patches (“tail white”) in male Cerulean Warblers (Setophaga cerulea) and whether variation in patch size could serve as a signal. We hypothesized that the size of tail white patches in males acts as an honest signal of quality, with larger white patches indicating high quality males. We measured and compared the area of tail white to four estimates of quality (age, structural size, body mass, and blood parasite load) in 71 male Cerulean Warblers at the Queen’s University Biological Station in eastern Ontario. We found that males 2 years old or older had significantly larger tail white patches than 1 year old males, and that structurally larger males (estimated by wing length) had significantly larger tail white patches than smaller males. Our best-performing statistical model suggested that heavier individuals had larger areas of tail white, but this relationship depended on wing length: white positively covaried with body mass in smaller individuals (shorter wings), but not in larger individuals. Our findings suggest that size of tail white patches may provide information on some, but not all, aspects of quality of male Cerulean Warblers; however, we do not know if this information is perceived and used by other Cerulean Warblers in nature.
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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) | 0.015 | 0.004 |
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".