Essential and non-essential trace elements in fish consumed by indigenous peoples of the European Russian Arctic
Bibliographic record
Abstract
In present study, the analyses of essential [copper (Cu), cobalt (Co), selenium (Se) and zinc (Zn)] and non-essential elements [mercury (Hg), lead (Pb), cadmium (Cd) and arsenic (As)] in 7 fish species consumed by the indigenous people of the European Russia Arctic were conducted. The Nenets Autonomous Region, which is located in the north-eastern part of European Russia, was chosen as a Region of interest. Within it, the Nenets indigenous group (n = 6000) constitutes approximately 10% of the total population. Nearly all of the Nenets live a traditional life with fish caught in the local waters as a subsistence resource. We found that northern pike contained twice the amount of Hg compared with roach, and 3-4 times more than other fish species commonly consumed in the Russian Arctic (namely, Arctic char, pink salmon, navaga, humpback whitefish and inconnu). Fish Hg concentrations were relatively low, but comparable to those reported in other investigations that illustrate a decreasing south-to-north trend in fish Hg concentrations. In the current study, northern pike is the only species for which Hg bioaccumulated significantly. In all fish species, both Cd and Pb were present in considerably lower concentrations than Hg. The total As concentrations observed are similar to those previously published, and it is assumed to be present primarily in non-toxic organic forms. All fish tissues were rich in the essential elements Se, Cu and Zn and, dependent on the amount fish consumed, may contribute significantly to the nutritional intake by indigenous Arctic peoples. We observed large significant differences in the molar Se/Hg ratios, which ranged from 2.3 for northern pike to 71.1 for pink salmon. Values of the latter <1 may increase the toxic potential of Hg, while those >1 appear to enhance the protection against Hg toxicity.
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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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".