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Record W2626612493 · doi:10.1002/2017gl073359

Evidence for marine biogenic influence on summertime Arctic aerosol

2017· article· en· W2626612493 on OpenAlexafffund
Megan D. Willis, Franziska Köllner, Julia Burkart, Heiko Bozem, Jennie L. Thomas, Johannes Schneider, Amir A. Aliabadi, Peter Hoor, Hannes Schulz, Andreas Herber, W. R. Leaitch, Jonathan P. D. Abbatt

Bibliographic record

VenueGeophysical Research Letters · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of GuelphEnvironment and Climate Change CanadaUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAerosolSulfateSea salt aerosolSea saltSulfate aerosolArcticEnvironmental scienceAtmospheric sciencesCloud condensation nucleiEnvironmental chemistryClimatologyOceanographyChemistryMeteorologyGeologyGeography

Abstract

fetched live from OpenAlex

Abstract We present vertically resolved observations of aerosol composition during pristine summertime Arctic background conditions. The methansulfonic acid (MSA)‐to‐sulfate ratio peaked near the surface (mean 0.10), indicating a contribution from ocean‐derived biogenic sulfur. Similarly, the organic aerosol (OA)‐to‐sulfate ratio increased toward the surface (mean 2.0). Both MSA‐to‐sulfate and OA‐to‐sulfate ratios were significantly correlated with FLEXPART‐WRF‐predicted air mass residence time over open water, indicating marine‐influenced OA. External mixing of sea salt aerosol from a larger number fraction of organic, sulfate, and amine‐containing particles, together with low wind speeds (median 4.7 m s −1 ), suggests a role for secondary organic aerosol formation. Cloud condensation nuclei concentrations were nearly constant (∼120 cm −3 ) when the OA fraction was <60% and increased to 350 cm −3 when the organic fraction was larger and residence times over open water were longer. Our observations illustrate the importance of marine‐influenced OA under Arctic background conditions, which are likely to change as the Arctic transitions to larger areas of open water.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.103
GPT teacher head0.347
Teacher spread0.245 · 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.

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

Citations100
Published2017
Admission routes2
Has abstractyes

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