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Record W2953421689 · doi:10.3390/atmos10070349

Biogenic Aerosol in the Arctic from Eight Years of MSA Data from Ny Ålesund (Svalbard Islands) and Thule (Greenland)

2019· article· en· W2953421689 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAtmosphere · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsAerosolCloud condensation nucleiEnvironmental sciencePhytoplanktonAtmosphere (unit)Sea iceOceanographyMethanesulfonic acidAtmospheric sciencesArcticDimethyl sulfideIce nucleusNutrientGeologyChemistryGeographyMeteorologyBiologyEcology

Abstract

fetched live from OpenAlex

In remote marine areas, biogenic productivity and atmospheric particulate are coupled through dimethylsulfide (DMS) emission by phytoplankton. Once in the atmosphere, the gaseous DMS is oxidized to produce H2SO4 and methanesulfonic acid (MSA); both species can affect the formation of cloud condensation nuclei. This study analyses eight years of biogenic aerosol evolution and variability at two Arctic sites: Thule (76.5° N, 68.8° W) and Ny Ålesund (78.9° N, 11.9° E). Sea ice plays a key role in determining the MSA concentration in polar regions. At the beginning of the melting season, in April, up to June, the biogenic aerosol concentration appears inversely correlated with sea ice extent and area, and positively correlated with the extent of the ice-free area in the marginal ice zone (IF-MIZ). The upper ocean stratification induced by sea ice melting might have a role in these correlations, since the springtime formation of this surface layer regulates the accumulation of phytoplankton and nutrients, allowing the DMS to escape from the sea to the atmosphere. The multiyear analysis reveals a progressive decrease in MSA concentration in May at Thule and an increase in July August at Ny Ålesund. Therefore, while the MSA seasonal evolution is mainly related with the sea ice retreat in April, May, and June, the IF-MIZ extent appears as the main factor affecting the longer-term behavior of MSA.

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.

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 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 score0.007
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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 head0.212
Teacher spread0.195 · 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