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 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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".