Quantifying corticosterone in feathers: validations for an emerging technique
Bibliographic record
Abstract
Feather corticosterone measurement is becoming a widespread tool for assessing avian physiology. Corticosterone is deposited into feathers during growth and provides integrative and retrospective measures of an individual's hypothalamic-pituitary-adrenal (HPA) axis function. Although researchers across disciplines have been measuring feather corticosterone for the past decade, there are still many issues with the extraction and measurement of corticosterone from feathers. In this paper, we provide several directives for refining the methodology for feather hormone analysis. We compare parallelism between the standard curve and serially diluted feather tissue from wild turkeys, Canada jays, and black-capped chickadees to demonstrate the wide applicability across species. Through a series of validations, we compare methods for feather preparation, sample filtration and extract reconstitution prior to corticosterone quantification using a radioimmunoassay. Higher corticosterone yields were achieved following pulverization of the feather however, more variation between replicates was observed. Removal of the rachis also increased the amount of corticosterone detected per unit mass while glass versus paper filters had no effect, and using ethanol in the reconstution buffer decreased intra-assay variation. With these findings and continued methodological refinement, feather corticosterone has the potential to be a powerful tool for both ecologists and physiologists working with historical and contemporary specimens.
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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 | 0.025 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".