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Record W4406509932 · doi:10.1039/d5fd00005j

Transport of continental particulate over the Labrador Sea and entrainment are important pathways for glaciation of remote marine clouds

2025· article· en· W4406509932 on OpenAlexaboutno aff
Hugh Coe, Nicholas Marsden, Michael Biggart, Keith Bower, T. W. Choularton, Michael S. Flynn, M. W. Gallagher, Kezhen Hu, Gary Lloyd, G. J. Nott, Paul R. Field, Benjamin J. Murray

Bibliographic record

VenueFaraday Discussions · 2025
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsnot available
FundersHORIZON EUROPE Framework ProgrammeNatural Environment Research CouncilUniversity of LeedsSight Research UKUK Research and Innovation
KeywordsOceanographyEntrainment (biomusicology)Glacial periodGeologyEnvironmental sciencePaleontology

Abstract

fetched live from OpenAlex

observations of the fractional ice water content. Three different air mass regimes were sampled: northerly winds in both the marine boundary layer and the lower free troposphere; westerly winds from Canada in both the marine boundary layer and the free troposphere; and periods when the boundary layer winds were northerly but the air immediately above the boundary layer was from continental Canada. When the air in the boundary layer and free troposphere was from the north, most clouds were in the liquid phase, however, considerably more glaciation was observed when the air immediately above the boundary layer clouds was from Canada regardless of the flow direction in the boundary layer. Sea salt particles dominate the observed out of cloud aerosol particle population and liquid cloud particle residuals. However, in the detected mixed phase and ice cloud particle residuals dust and bioaerosol particles were substantial in number. Since these are known to be effective ice-nucleating particles, the observations suggest that long range transport of continental air and entrainment is an important pathway for the supply of aerosol to the remote Arctic boundary layer.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.296

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 science0.0000.000
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 head0.008
GPT teacher head0.213
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; 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

Citations0
Published2025
Admission routes1
Has abstractyes

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