Data from: Evidence of degradation of hair corticosterone in museum specimens
Bibliographic record
Abstract
Researchers increasingly rely on non-invasive physiological indices, such as glucocorticoid (GC) levels, to interpret how vertebrates respond to changes in their environment. Recently, hair GCs have been of particular interest, because they are presumed stable over long periods of storage, which may facilitate the study of large-scale spatial and temporal patterns of stress in mammals. In the current study, we evaluated the stability of hair corticosterone levels in museum specimens, and the potential effects of different museum curation treatments. Using deer mouse (Peromyscus maniculatus) specimens collected from Vancouver Island (11 sites, 82 individuals) over 76 years, we found that specimens collected earlier in the 20th century had lower hair corticosterone than more recently collected specimens. These results suggest that hair hormone levels may not be stable over decades of storage time. We then subjected hair samples collected from white-footed mouse (Peromyscus leucopus, n = 36) to 3 different museum curation treatments, and found that borax lowered hair corticosterone levels relative to control samples, but air drying samples, or treating them with turpentine had no effect. Our results present a source of concern for the use of museum specimens for hair hormone analysis, and for studying long term trends in glucocorticoid levels.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.015 |
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".