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Record W318335603

An Observational Study of the Efficiency of Activation of Accumulation-Mode Particles in Warm Continental Stratiform Clouds

2024· article· en· W318335603 on OpenAlexaff
Noor V. Gillani, P. H. Daum, S.E. Schwartz, W Richard Leaitch, J. W. Strapp, George A. Isaac

Bibliographic record

VenueOSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsEnvironment and Climate Change Canada
FundersElectric Power Research InstituteU.S. Department of Energy
KeywordsPhysicsAtmospheric sciencesAnalytical Chemistry (journal)MeteorologyAstrophysicsChemistryAtomic physics
DOInot available

Abstract

fetched live from OpenAlex

Continuous aircraft measurements of the in-cloud number concentrations (N) of cloud droplets (CD, 2 - 35 μm diameter) and accumulation-mode particles (AMP, 0. 17 - 2.07 μm diam) have been used to study the efficiency of activation of AMP in warm continental stratiform clouds near Syracuse NY during Fall 1984. The efficiency is defined as the activated fraction (F) of all measured particles. Thus, F = Ncd/Ntot where Ntot = Ncd+Namp. The primary focus in this paper is on the dependence of F on Ntot. In the interior of clouds, two distinct regimes of the state of activation of AMP were observed. For Ntot < 600 cm-3, F was largely close to unity and relatively insensitive to Ntot. Such conditions prevailed in relatively Cold airmasses of northerly origin. For Ntot > 800 cm-3, F tended to decrease with increasing Ntot. This decrease was greatest in a stable stratus deck embedded in a warm, moist airmass of southerly origin. The spatial variation of F is used to explore the non-uniform state of activation in the clouds. In general, F was lower in cloud edges and in the upper portions of the clouds.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.069
GPT teacher head0.334
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2024
Admission routes1
Has abstractyes

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