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Record W4391249064 · doi:10.1126/sciadv.adi7760

Large mercury release from the Greenland Ice Sheet invalidated

2024· article· en· W4391249064 on OpenAlexaff
Christian Juncher Jørgensen, Jens Søndergaard, Martin Mørk Larsen, Kristian K. Kjeldsen, Diogo Rosa, Sarah Elise Sapper, Lars‐Éric Heimbürger‐Boavida, Stephen G. Kohler, Fei Wang, Zhiyuan Gao, Debbie Armstrong, Christian Nyrop Albers

Bibliographic record

VenueScience Advances · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of Manitoba
FundersAarhus Universitet
KeywordsGreenland ice sheetMeltwaterMercury (programming language)GroenlandiaGlacial periodIce sheetArcticGlacierBedrockEnvironmental scienceOceanographyGeologyPhysical geographyIce coreGeomorphologyGeography

Abstract

fetched live from OpenAlex

The major input of mercury (Hg) to the Arctic is normally ascribed to long-range transport of anthropogenic Hg emissions. Recently, alarming concentrations of Hg in meltwater from the Greenland Ice Sheet (GrIS) were reported with bedrock as the proposed source. Reported Hg concentrations were 100 to 1000 times higher than in known freshwater systems of Greenland, calling for independent validation of the extraordinary concentrations and conclusions. Here, we present measurements of Hg at 21 glacial outlets in West Greenland showing that extreme Hg concentrations cannot be reproduced. In contrast, we find that meltwater from below the GrIS is very low in Hg, has minor implications for the global Hg budget, and pose only a very limited risk for local communities and the natural environment of Greenland.

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)0.000
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 score0.042
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.017
GPT teacher head0.291
Teacher spread0.273 · 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

Citations11
Published2024
Admission routes1
Has abstractyes

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