A novel method for the measurement of glucocorticoids in dermal secretions of amphibians
Bibliographic record
Abstract
Amphibians have been declining in both diversity and abundance due in large part to habitat degradation and the prevalence of emerging diseases. Although stressors can suppress the immune system, affecting an individual's health and susceptibility to pathogens, established methods for directly collecting stress hormones are not suitable for rapid field use or for use on threatened and endangered species. To overcome these challenges, we are developing an innovative method to collect and measure amphibian glucocorticoid secretions using non-invasive dermal swabs. We tested this methodology using multiple terrestrial, semi-aquatic and fully aquatic species. We swabbed the dorsal side of each animal six times and then induced a stressor of either hand-restraint, ACTH injection, or saline as a control. We then repeated swab collection immediately after the stressor and at 15, 30, 45, 60, 90 and 120 min intervals. Cortisol enzyme immunoassay detected changes in cortisol post-stressor. We also tested this methodology in the field and were successfully able to detect glucocorticoids from multiple species at varying life stages. When using in the field, capture technique should be considered since it may impact stress levels in certain species. Upon further testing, this novel method may be used to greatly increase our understanding of amphibian health especially as disease and environmental changes continue to impact fragile populations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".