Mercury and cortisol in Western Hudson Bay polar bear hair
Bibliographic record
Abstract
Non-invasive methods of assessing animal health and life history are becoming increasingly popular in wildlife research; hair samples from polar bears (Ursus maritimus), are being used to study an ever broader range of anthropogenic and endocrine compounds. A number of contaminants are known to disrupt endocrine function in polar bears. However, the relationship between mercury and cortisol remains unknown, although mercury is an endocrine disruptor in other species. Here, we examine the relationship between concentrations of cortisol and total mercury (THg) analyzed in guard hair from 378 polar bears (184 females, 194 males) sampled in Western Hudson Bay, 2004-2012. The difference in mean cortisol concentration between female (0.8 ± 0.6 pg/mg) and male (0.7 ± 0.5 pg/mg) polar bears bordered on significance (p = 0.054). However, mean mercury concentration was significantly greater (p = 0.009) in females (4.7 ± 1.4 μg/g) than males (4.3 ± 1.2 μg/g). Hair cortisol in males was significantly influenced by mercury, age, and fatness, as well as interactions between mercury and year, mercury and fatness, and year and fatness (all: p < 0.03) (multiple regression analysis, whole model: r(2) = 0.14, F(7,185) = 4.43, p = 0.0001). Fatness was the only significant variable in the multiple regression analysis for females (r(2) = 0.06, F(1,182) = 13.0, p = 0.0004). In conclusion, a significant, but complex, relationship was found between mercury and cortisol concentrations in hair from male, but not female, polar bears.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".