Influence of Carbon and Lipid Sources on Variation of MercuryAnd Other Trace Elements in Polar Bears (Ursus Maritimus)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the present study, the authors investigated the influence of carbon and lipid sources on regional differences in liver trace element (As, Cd, Cu, total Hg, Mn, Pb, Rb, Se, and Zn) concentrations measured in polar bears (Ursus maritimus) (n=121) from 10 Alaskan, Canadian Arctic, and East Greenland subpopulations. Carbon and lipid sources were assessed using δ13C in muscle tissue and fatty acid (FA) profiles in subcutaneous adipose tissue as chemical tracers. A negative relationship between total Hg and δ13C suggested that polar bears feeding in areas with higher riverine inputs of terrestrial carbon accumulate more Hg than bears feeding in areas with lower freshwater input. Mercury concentrations were also positively related to the FA 20:1n-9, which is biosynthesized in large amounts in Calanus copepods. This result raises the hypothesis that Calanus glacialis are an important link in the uptake of Hg in the marine food web and ultimately in polar bears. Unadjusted total Hg, Se, and As concentrations showed greater geographical variation among polar bear subpopulations compared with concentrations adjusted for carbon and lipid sources. The Hg concentrations adjusted for carbon and lipid sources in Bering–Chukchi Sea polar bear liver tissue remained the lowest among subpopulations. Based on these findings, the authors suggest that carbon and lipid sources for polar bears should be taken into account when one is assessing spatial and temporal trends of long-range transported trace elements.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it