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Record W2020653590 · doi:10.1021/es4035655

A Chinese Imprint in Insoluble Pollutants Recently Deposited in Central Greenland As Indicated by Lead Isotopes

2013· article· en· W2020653590 on OpenAlexaboutno aff
Aloys Bory, Wafa Abouchami, Stephen J.G. Galer, Anders Svensson, John N. Christensen, Pierre E. Biscaye

Bibliographic record

VenueEnvironmental Science & Technology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
FundersLamont-Doherty Earth Observatory, Columbia UniversityU.S. Department of EnergyLawrence Berkeley National LaboratoryNational Science Foundation
KeywordsPollutantLead (geology)IsotopeEnvironmental chemistryEnvironmental scienceChemistryGeologyPaleontologyPhysicsNuclear physics

Abstract

fetched live from OpenAlex

A unique ∼ 10 year record of the lead isotopic composition of airborne insoluble particulate matter deposited in central Greenland was extracted from recent snow layers at NorthGRIP (75.1°N, 042.3°W; elevation 2,959 m), spanning the years 1989-2001. Comparison with lead isotopic signatures of both natural and anthropogenic northern hemisphere (NH) aerosol sources shows that human activities must have accounted for most of the insoluble lead deposited on Greenland during the late 1990 s, exceeding by far the natural contribution from large Asian mineral dust inputs. Lead isotopes imply predominance with time of European/Canadian sources over U.S.-derived lead, with an admixed signature typical of Chinese anthropogenic lead sources. The relative contribution of the latter shows a marked seasonal increase during spring. Our record also suggests that China's weight in the overall supply of insoluble pollutants deposited on Greenland was growing over the past decade of the 20th century.

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 categoriesMeta-epidemiology (narrow), Science 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
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
Bibliometrics0.0010.004
Science and technology studies0.0000.003
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.003
GPT teacher head0.208
Teacher spread0.205 · 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

Citations66
Published2013
Admission routes1
Has abstractyes

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