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Record W2129339840 · doi:10.1256/qj.03.153

Liquid fraction in stratiform mixed‐phase clouds from <i>in situ</i> observations

2004· article· en· W2129339840 on OpenAlexafffund
Faisal S. Boudala, George A. Isaac, Stewart G. Cober, Qiang Fu

Bibliographic record

VenueQuarterly Journal of the Royal Meteorological Society · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsDalhousie University
FundersCanadian Foundation for Climate and Atmospheric SciencesNational Science Foundation
KeywordsFraction (chemistry)Liquid water contentIce crystalsCloud fractionAtmospheric sciencesPhase (matter)Environmental scienceMass fractionMixed phaseMean radiant temperatureLiquid waterMaterials scienceMeteorologyClimate changeThermodynamicsGeologyChemistryPhysicsCloud computingCloud coverChromatography

Abstract

fetched live from OpenAlex

Abstract Liquid fractions in mixed‐phase clouds have been analysed using aircraft measurements taken in mid‐ and high latitude stratiform clouds. The liquid fraction generally increases with temperature but has a minimum at about −15°C, where the maximum ice crystal growth based on vapour deposition would be expected. The mean liquid fraction also depends on total water content. This suggests that segregation of cloud phase based on a simple linear relationship of phase fraction (ice or liquid) with temperature, as is used in some climate models, may be unrealistic. Parametrizations of mean liquid fraction in terms of temperature and total water content, and in terms of temperature alone, have been developed based on data averaged at 10 s resolution (1 km). These parametrizations agree reasonably well with the observations. Copyright © 2004 Royal Meteorological Society

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)0.000
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 score0.500
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.015
GPT teacher head0.239
Teacher spread0.224 · 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

Citations46
Published2004
Admission routes2
Has abstractyes

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