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Record W2097240221 · doi:10.1175/bams-d-11-00123.1

In Situ, Airborne Instrumentation: Addressing and Solving Measurement Problems in Ice Clouds

2011· article· en· W2097240221 on OpenAlexaff
D. Baumgardner, L. M. Avallone, Aaron Bansemer, Stephan Borrmann, Philip R. Brown, Ulrich Bundke, P. Y. Chuang, Daniel J. Cziczo, Paul R. Field, M. W. Gallagher, J.‐F. Gayet, Andrew J. Heymsfield, Alexei Korolev, Martina Krämer, Greg M. McFarquhar, Stephan Mertes, Ottmar Möhler, Sara Lance, P. Lawson, Markus D. Petters, Kerri A. Pratt, Greg Roberts, D. Rogers, O. Stetzer, Jeffrey L. Stith, W. Strapp, C. H. Twohy, Manfred Wendisch

Bibliographic record

VenueBulletin of the American Meteorological Society · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric aerosols and clouds
Canadian institutionsEnvironment and Climate Change Canada
FundersNatural Environment Research CouncilSight Research UKNational Aeronautics and Space AdministrationU.S. Department of EnergyNational Science Foundation
KeywordsInstrumentation (computer programming)Atmospheric researchCloud computingIce formationSystems engineeringMeteorologyIce cloudEnvironmental scienceRemote sensingComputer scienceAeronauticsEngineeringGeographyGeologyAtmospheric sciences

Abstract

fetched live from OpenAlex

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not.The documents may come from teaching and research institutions in France or abroad, or from public

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)0.007
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.232
Teacher spread0.196 · 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 designBench or experimental
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

Citations50
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueBulletin of the American Meteorological SocietySame topicAtmospheric aerosols and cloudsFrench-language works237,207