Concentrations of mercury and polychlorinated biphenyls in blood of Southern Beaufort Sea polar bears (<i>Ursus maritimus</i>) during spring: variations with lipids and stable isotope (δ<sup>15</sup>N, δ<sup>13</sup>C) values
Bibliographic record
Abstract
Polar bears ( Ursus maritimus Phipps, 1774) are exposed to heavy metal and lipophilic contaminants that are known to bioaccumulate and biomagnify. Few studies concurrently report both chemical classes in the same individuals and are thus unable to assess drivers of observed tissue concentrations, and the potential adverse biological responses to combined exposures. We examined blood concentrations of mercury (Hg) and the sum of seven polychlorinated biphenyls (Σ7PCB) from free-ranging Southern Beaufort Sea polar bears to assess which factors contributed to variations among cohorts (adult males, adult females, young) during spring. Concentrations of Hg ranged from 10.3 to 228.0 ng/g wet mass, but mean concentrations were similar between males and females independent of age. Concentrations of Σ7PCB (range 2.0–132.8 ng/g wet mass) were greater among females and young than among males. Toxicant concentrations were related to packed cell δ15N, an estimate of trophic position, after the inclusion of packed cell δ13C. Concentrations of Σ7PCB were also positively correlated with concentrations of neutral lipids (triglycerides and free fatty acids) and inversely correlated to body condition indices. Elevated concentrations of toxicants and lower body condition indices in females and young compared with males may be a sentinel to a changing arctic environment. Further assessment of the potential adverse health impacts of contaminants and nutritional stress in these cohorts is warranted.
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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 | 0.000 |
| 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".