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Record W1513821594 · doi:10.2166/wst.2000.0566

Sources, trends, implications and remediation of mercury contamination of lakes in remote areas of Canada

2000· article· en· W1513821594 on OpenAlexaffabout
L Trip, R J Allan

Bibliographic record

VenueWater Science & Technology · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsMercury (programming language)Environmental scienceBiotaEnvironmental remediationRemedial actionDeposition (geology)SedimentContaminationEnvironmental protectionEnvironmental engineeringHydrology (agriculture)Environmental chemistryEcologyGeologyChemistry

Abstract

fetched live from OpenAlex

The long-range atmospheric transport and deposition of mercury (Hg) into lakes has become a subject of increasing interest. In Canada today, the main sources of anthropogenic, atmospheric Hg are considered to be power stations and waste incinerators in the United States and Europe. Increases in deposition of Hg have been recorded in lake sediment cores from many parts of Canada. Where Hg input to lakes from local sources in Canada has been reduced, concentrations in lake sediments and lake biota have declined. However, in many remote lake, fish consumption advisories are still in effect for Hg. Debate continues over the sources of this mercury, whether long-range anthropogenic, atmospheric or natural. Many remedial actions have been taken in the past, and continue to be taken, to reduce Hg releases to the environment in Canada.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.007
GPT teacher head0.222
Teacher spread0.215 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations8
Published2000
Admission routes2
Has abstractyes

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