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Record W1975630899 · doi:10.1021/es202068b

Mercury Export from the Yukon River Basin and Potential Response to a Changing Climate

2011· article· en· W1975630899 on OpenAlexaboutno aff
Paul F. Schuster, Robert G. Striegl, George R. Aiken, David P. Krabbenhoft, John F. DeWild, Kenna D. Butler, Ben Kamark, M. Dornblaser

Bibliographic record

VenueEnvironmental Science & Technology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
FundersU.S. Geological Survey
KeywordsPermafrostMercury (programming language)MethylmercuryEnvironmental scienceDrainage basinParticulatesTotal organic carbonBiotaHydrology (agriculture)WatershedEnvironmental chemistryGeologyOceanographyChemistryEcology

Abstract

fetched live from OpenAlex

We measured mercury (Hg) concentrations and calculated export and yield from the Yukon River Basin (YRB) to quantify Hg flux from a large, permafrost-dominated, high-latitude watershed. Exports of Hg averaged 4400 kg Hg yr(-1). The average annual yield for the YRB during the study period was 5.17 μg m(-2) yr(-1), which is 3-32 times more than Hg yields reported for 8 other major northern hemisphere river basins. The vast majority (90%) of Hg export is associated with particulates. Half of the annual export of Hg occurred during the spring with about 80% of 34 samples exceeding the U.S. EPA Hg standard for adverse chronic effects to biota. Dissolved and particulate organic carbon exports explained 81% and 50%, respectively, of the variance in Hg exports, and both were significantly (p < 0.001) correlated with water discharge. Recent measurements indicate that permafrost contains a substantial reservoir of Hg. Consequently, climate warming will likely accelerate the mobilization of Hg from thawing permafrost increasing the export of organic carbon associated Hg and thus potentially exacerbating the production of bioavailable methylmercury from permafrost-dominated northern river basins.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.002
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 head0.012
GPT teacher head0.222
Teacher spread0.210 · 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 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

Citations137
Published2011
Admission routes1
Has abstractyes

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