MétaCan
Menu
Back to cohort
Record W2999216539 · doi:10.1073/pnas.1906930117

Global warming accelerates uptake of atmospheric mercury in regions experiencing glacier retreat

2020· article· en· W2999216539 on OpenAlexaff
Xun Wang, Ji Luo, Wei Yuan, Che‐Jen Lin, Fei Wang, Chen Liu, Genxu Wang, Xinbin Feng

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsGlacierEnvironmental scienceGlobal warmingEcosystemMercury (programming language)Climate changeAtmospheric sciencesPhysical geographyClimatologyGeologyOceanographyEcologyGeography

Abstract

fetched live from OpenAlex

) from the atmosphere. The accelerated uptake enriches the Hg pool size in glacier-retreated areas by a factor of ∼10 compared with the original pool size in the glacier. Through an assessment of Hg source-sink relationship observed in documented glacier-retreated areas in the world (7 sites of tundra/steppe succession and 5 sites of forest succession), we estimate that 400 to 600 Mg of Hg has been accumulated in glacier-retreated areas (5‰ of the global land surface) since the Little Ice Age (∼1850). By 2100, an additional ∼300 Mg of Hg will be sequestered from the atmosphere in glacier-retreated regions globally, which is ∼3 times the total Hg mass loss by meltwater efflux (∼95 Mg) in alpine and subpolar glacier regions. The recapturing of atmospheric Hg by vegetation in glacier-retreated areas is not accounted for in current global Hg models. Similar processes are likely to occur in other regions that experience increased vegetation due to climate or land use changes, which need to be considered in the assessment of global Hg cycling.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.187
Threshold uncertainty score0.342

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.061
GPT teacher head0.311
Teacher spread0.250 · 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 teacher head, 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

Citations102
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicMercury impact and mitigation studiesFrench-language works237,207