Why the English–Wabigoon river system is still polluted by mercury 57 years after its contamination
Bibliographic record
Abstract
Between 1962 and 1969, 10 tonnes of mercury were discharged from a chlor-alkali plant in Dryden, Ontario, to the English–Wabigoon River. Present-day fish mercury concentrations are amongst the highest recorded in Canada. In 2017, the Grassy Narrows Science Team found no evidence of ongoing discharges from the plant site to the river water, even though large quantities of mercury remain at the site. Instead, our data suggest that ongoing erosion of high mercury particles by the river, as it meanders through contaminated floodplains, is responsible for present-day transport of mercury to Clay Lake and to Ball Lake, located 154 km downstream. In Clay Lake, surface sediment total mercury concentrations and inflow water concentrations are still about 15 times above background (86 km downstream), and in Ball Lake mercury concentrations in sediments appeared to be still increasing. The remobilization of legacy inorganic mercury from riverbank erosion between Dryden and Clay Lake stimulates methyl mercury production there, in Clay Lake, and in Ball Lake. The large quantities of methyl mercury produced between Dryden and Clay Lake are mostly dissolved in water and are swept downstream, elevating concentrations in water and biota throughout the system. Several options for remediating the ongoing contamination are discussed.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".