Mercury in Ringed Seals (<i>Pusa hispida</i>) from the Canadian Arctic in Relation to Time and Climate Parameters
Bibliographic record
Abstract
Mercury is found in Arctic marine mammals that are important in the diet of northern Indigenous peoples. The objectives of the present long-term study, spanning a 45-yr period, were to 1) investigate the temporal trends of total mercury (THg; muscle and liver) and selenium (Se; liver) in ringed seals (Pusa hispida) from different regions of the Canadian Arctic; and 2) examine possible relationships with age, diet, and climate parameters such as air temperature, precipitation, climatic indices, and ice-coverage. Ringed seals were collected by hunters in northern communities in the Beaufort Sea, Central Arctic, Eastern Baffin Island, Hudson Bay, and Ungava/Nunatsiavut regions (Canada) between 1972 and 2017. Mercury levels did not change through time in seal liver, but THg levels in muscle decreased in seals from Hudson Bay (-0.91%/yr) and Ungava/Nunatsiavut (-1.30%/yr). Carbon stable isotope values in seal muscle decreased significantly through time in 4 regions. Selenium-to-THg ratios were found to be >1 for all years and regions. Variation partitioning analyses across regions indicated that THg trends in seals were mostly explained by age (7.3-21.7%), climate parameters (3.5-12.5%), and diet (up to 9%); climate indices (i.e., Arctic and North Atlantic Oscillations, Pacific/North American pattern) explained the majority of the climate portion. The THg levels had a positive relationship with Arctic Oscillation for multiple regions. Associations of THg with air temperature, total precipitation, and sea-ice coverage, as well as with North Atlantic Oscillation and Pacific/North American pattern were found to vary with tissue type and geographical area. Environ Toxicol Chem 2020;39:2462-2474. © 2020 Her Majesty the Queen in Right of Canada. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. Reproduced with the permission of the Minister of Fisheries and Oceans Canada.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".