Tracking stress: localisation, deposition and stability of corticosterone in feathers
Bibliographic record
Abstract
How animals cope with stressors is an important determinant of their well being and fitness. Understanding what environmental perturbations are perceived as stressors, and quantifying how they are responded to, how often they occur and the negative consequences of exposure to glucocorticoids, has been problematic and limited to short-term physiological measures. By contrast, the quantification of corticosterone (CORT) in feathers represents a long-term, integrated measure of hypothalamic-pituitary-adrenal activity. In the present study, we show that by understanding how the hormone is deposited in feathers, in combination with specific sampling protocols, one can identify localised patterns of CORT deposition that reveal different temporal patterns of a bird's response to stressors. CORT in feathers appears to be stable over time, is resistant to heat exposure and is useful in determining both the overall exposure of the bird to the hormone over days or weeks, as well as identifying discrete, punctuated, stressful events. Variation in feather CORT can also be examined among individuals of a population at one point in time, as well as over years by using museum specimens. The ability to track stress over time allows for new questions to be asked about the health and ecology of birds and their environment.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".