Spatial Trends and Historical Deposition of Mercury in Eastern and Northern Canada Inferred from Lake Sediment Cores
Bibliographic record
Abstract
Recent and historical deposition of mercury (Hg) was examined over a broad geographic area from southwestern Northwest Territories to Labrador and from the U.S. Northeast to northern Ellesmere Island using dated sediment cores from 50 lakes (18 in midlatitudes (41-50 degrees N), 14 subarctic (51-64 degrees N) and 18 in the Arctic (65-83 degrees N)). Distinct increases of Hg overtime were observed in 76% of Arctic, 86% of subarctic and 100% of midlatitude cores. Subsurface maxima in Hg depositional fluxes (microg m(-2) y(-1)) were observed in only 28% of midlatitude lakes and 18% of arctic lakes, indicating little recent reduction of inputs. Anthropogenic Hg fluxes adjusted for sediment focusing and changes in sedimentation rates (deltaF(adj,F)) ranged from -22.9 to 61 microg m(-2) y(-1) and were negatively correlated (r = -0.57, P < 0.001) with latitude. Hg flux ratios (FRs; post-1990)/pre-1850) ranged from 0.5 to 7.7. The latitudinal trend for Hg deltaF(adj,F) values showed excellent agreement with predictions of the global mercury model, GRAHM for the geographic location of each lake (r = 0.933, P < 0.001). The results are consistent with a scenario of slow atmospheric oxidation of mercury, and slow deposition of reactive mercury emissions, declining with increasing latitude away from emission sources in the midlatitudes, and support the view that there are significant anthropogenic Hg inputs in the Arctic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".