Noninvasive Monitoring of Fecal Cortisol Metabolites in the Eastern Chipmunk (<i>Tamias striatus</i>): Validation and Comparison of Two Enzyme Immunoassays
Bibliographic record
Abstract
Monitoring fecal glucocorticoid metabolites in wild animals, using enzyme immunoassays, enables the study of endocrinological patterns relevant to ecology and evolution. While some researchers use antibodies against the parent hormone (which is typically absent from fecal samples), others advocate the use of antibodies designed to detect glucocorticoid metabolites. We validated two assays to monitor fecal cortisol metabolites in the eastern chipmunk (Tamias striatus). We compared an antibody produced against cortisol and one produced against 5α-pregnane-3β, 11β, 21-triol-20-one using a radiometabolism study and an injection with adrenocorticotropic hormone (ACTH). Most cortisol metabolites were excreted in the urine (∼83%). Peak excretion in the feces occurred 8 h after injection. Both assays detected an increase in fecal cortisol metabolite levels after injection of ACTH. Males, but not females, exhibited a circadian variation in metabolite levels. The sexes did not exhibit any difference over the time course and route of excretion or the relative increase in fecal cortisol metabolite levels after ACTH injection. The cortisol assay displayed higher reactivity to ACTH injection relative to baseline than did the metabolite assay. While both antibodies gave comparable results, the cortisol antibody was more sensitive to changes in plasma cortisol levels in eastern chipmunks.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".