Low and Declining Mercury in Arctic Russian Rivers
Bibliographic record
Abstract
Mercury (Hg) dynamics in the Arctic is receiving increasing attention, but further understanding is limited by a lack of studies in Russia, which encompasses the majority of the pan-Arctic watershed. This study reports Hg concentrations and trends in burbot (Lota lota) from the Lena and Mezen Rivers in the Russian Arctic, and assesses the extent to which they differ from those found in burbot in arctic rivers elsewhere. Mercury concentrations in burbot in the Lena and Mezen Rivers were found to be generally lower than in 23 other locations, most of which are in the Mackenzie River Basin (Canada). Mercury concentrations in burbot in the Lena and Mezen Rivers also were found to have been declining at an annual rate of 2.3% while they have been increasing in the Mackenzie River Basin at annual rates between 2.2 and 5.1% during roughly the same time period. These contrasting patterns in Hg in burbot across the pan-Arctic may be explained by geographic heterogeneity in controlling processes, including riverine particulate material loads, historically changing atmospheric inputs, postdepositional processes, and climate change impacts.
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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".