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Record W3187523415 · doi:10.1016/0967-0653(96)90976-x

10.1016/0967-0653(96)90976-x

2000· article· en· W3187523415 on OpenAlexvenueno aff

Bibliographic record

VenueTime to knit · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsnot available
Fundersnot available
KeywordsAerosolCloud condensation nucleiAtmospheric sciencesEnvironmental scienceCloud physicsSea salt aerosolPrecipitationAlbedo (alchemy)MeteorologyClimatologyCloud computingGeologyGeographySea salt

Abstract

fetched live from OpenAlex

Abstract Aerosol particles can act as cloud condensation nuclei and thereby influence the number and size of droplets in clouds. Consequently, anthropogenic particles have the potential to influence global climate by increasing cloud albedo and decreasing precipitation efficiencies. Enhanced cloud reflectances associated with increases in panicle number have been observed, but our understanding of these interactions has been hindered by incomplete empirical studies and models of limited scope. In this study, aerosol and droplet size distributions were measured on 13 research flights in stratiform clouds within 300 km west of the northern California coast. The chemical composition of the droplet solute was also assessed. Microphysical and chemical properties indicated that most of the clouds were influenced by pollution from the North American continent, but pristine marine clouds were sampled on one flight during westerly flow conditions. Data from this flight and another, representing a pristine and poll...

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.016
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.002
Science and technology studies0.0020.002
Scholarly communication0.0040.004
Open science0.0020.003
Research integrity0.0050.002
Insufficient payload (model declined to judge)0.9840.983

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 head0.004
GPT teacher head0.157
Teacher spread0.153 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2000
Admission routes1
Has abstractyes

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