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Record W4206485598 · doi:10.1139/facets-2021-0093

Why the English–Wabigoon river system is still polluted by mercury 57 years after its contamination

2021· article· en· W4206485598 on OpenAlexaffvenueabout
John W. M. Rudd, Carol A. Kelly, Patricia Sellers, R. J. Flett, B. E. Townsend

Bibliographic record

VenueFACETS · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsResearch Manitoba
Fundersnot available
KeywordsMercury (programming language)Environmental scienceHydrology (agriculture)ContaminationEnvironmental chemistryFloodplainSurface waterEnvironmental engineeringGeologyEcologyChemistry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.209
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.010
GPT teacher head0.222
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2021
Admission routes3
Has abstractyes

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