Comparison of mercury concentrations in landlocked, resident, and sea-run fish ( <i>Salvelinus</i> spp.) from Nunavut, Canada
Bibliographic record
Abstract
Mercury concentrations ([Hg]) in Arctic food fish often exceed guidelines for human subsistence consumption. Previous research on two food fish species, Arctic char (Salvelinus alpinus) and lake trout (Salvelinus namaycush), indicates that anadromous fish have lower [Hg] than nonanadromous fish, but there have been no intraregional comparisons. Also, no comparisons of [Hg] among anadromous (sea-run), resident (marine access but do not migrate), and landlocked (no marine access) life history types of Arctic char and lake trout have been published. Using intraregional data from 10 lakes in the West Kitikmeot area of Nunavut, Canada, we found that [Hg] varied significantly among species and life history types. Differences among species-life history types were best explained by age-at-size and C:N ratios (indicator of lipid); [Hg] was significantly and negatively related to both. At a standardized fork length of 500 mm, lake trout had significantly higher [Hg] (mean 0.17 µg/g wet wt) than Arctic char (0.09 µg/g). Anadromous and resident Arctic char had significantly lower [Hg] (each 0.04 µg/g) than landlocked Arctic char (0.19 µg/g). Anadromous lake trout had significantly lower [Hg] (0.12 µg/g) than resident lake trout (0.18 µg/g), but no significant difference in [Hg] was seen between landlocked lake trout (0.21 µg/g) and other life history types. Our results are relevant to human health assessments and consumption guidance and will inform models of Hg accumulation in Arctic fish.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".