Cortisol levels in blood and hair of unanesthetized grizzly bears ( <i>Ursus arctos</i> ) following intravenous cosyntropin injection
Bibliographic record
Abstract
Hair cortisol concentration (HCC) is being used increasingly to evaluate long-term stress in many mammalian species. Most of the cortisol is assumed to passively diffuse from circulating blood into hair follicles and gradually accumulate in growing hair. However, our research with free-ranging grizzly bears (Ursus arctos) suggests HCC increases significantly within several hours following capture, a time too brief to be explained by this mechanism alone. In this study with captive grizzly bears, we sought to determine if a brief spike in blood cortisol concentration, thus mimicking a single stressful event, would cause an increase in HCC over a 7-day period. To do this, we administered a single intravenous dose (5 μg/kg) of cosyntropin to three captive unanaesthetised adult female grizzly bears on two occasions, during April when hair growth was arrested and during August when hair was growing. In both trials, the cosyntropin caused a two-fold or greater increase in serum cortisol levels within 1 hr but did not appear to influence HCC at 1, 48, and 168 hr following cosyntropin administration. We conclude the cosyntropin-induced cortisol spike was likely insignificant when compared to the adrenocortical response that occurs in free-ranging bears when captured. We suggest further study with a larger sample of captive bears to evaluate the combined effects of anaesthesia and multiple doses of cosyntropin administered over several hours would better simulate the adrenocortical response of free-ranging grizzly bears during capture.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".