Sexing Hatching-year Yellow Warblers Using Plumage Characteristics
Bibliographic record
Abstract
Genetic techniques for sexing birds are potentially valuable tools for refining methods of sexing birds based on plumage.Here we use a female-specific microsatellite locus isolated from Yellow Warblers (Dendroica petechia) to evaluate a technique of sexing hatch-year (HY; < 2 mo of age) Yellow Warblers based on both overall brightness of the yellow of body plumage and the ratio of yellow to dull brown in the outer rectrix.All bright plumaged HY birds (n=21) were males and all dull plumaged HY birds (n=24) were females.All birds of intermediate bright plumage were male (n= 11) and all but three (of 14) intermediate pale birds were female.Canonical discriminant analysis based on measured proportions of yellow and dull brown in the outer rectrix correctly classified 85.7% of both females and males; 91.7% of females and 95.3% of males could be correctly classified with these criteria if intermediate plumages were excluded from the analysis.Using Munsell color codes improved the ability to differentiate sexes; Canonical discriminant analysis was able to correctly classify 100% of females and 92.9% of males using these criteria.Similar results were obtained when the discriminant analyses were performed on a jackknifed sample.Scores from 10 observers asked to sex birds based on rectrices improved from 76.3 to 87.3% by using the relative brightness of yellow in the rectrix and the presence of yellow along the narrow edge of this feather.Thus, the use of this sex-specific DNA marker has revealed a plumage characteristic which can be used to sex a significant component of HY birds of this species.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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 teacher head, 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".