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Record W2755388917

Ionization, Charging and Electric Field Effects on Cloud Particles in the CLOUD Experiment

2015· article· en· W2755388917 on OpenAlexvenueno aff
Leonid Nichman, Emma Järvinen, Rafael Wagner, J. R. Dorsey, António Dias, Sebastian Ehrhart, J. Kirkby, M. W. Gallagher, C. P. R. Saunders

Bibliographic record

VenueNPARC · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsCloud computingIonizationElectric fieldEnvironmental sciencePhysicsComputer scienceQuantum mechanicsIon
DOInot available

Abstract

fetched live from OpenAlex

Ice crystals and frozen droplets play an important role in atmospheric charging and electrification processes, particularly by collision and aggregation. The dynamics of charged particles in the atmosphere can be modulated by Galactic Cosmic Rays (GCR). High electric fields also affect the alignment of charged particles, allowing more time for interactions. The CLOUD (Cosmics Leaving OUtdoor Droplets) experiment at CERN has the ability to conduct ionization, charging and high electric field experiments on liquid or ice clouds created in the chamber by adiabatic pressure reductions. A pion secondary beam from the CERN Proton Synchrotron is used to ionize the molecules in the chamber, and Ar+ Corona Ion Generator for Atmospheric Research (CIGAR) is used to inject unipolar charged ions directly into the chamber. A pressurized airgun provides rapid pressure shocks inside the chamber and induces charged ice nucleation. The cloud chamber is accompanied by a variety of analysing instruments e.g. a 3View Cloud Particle Imager (3V-CPI) coupled with an induction ring, a Scattering Intensity Measurements for the Optical detection of icE (SIMONE) and a Nano-aerosol and Air Ion Spectrometer (NAIS). Using adiabatic expansion and high electric fields we can replicate the ideal conditions for adhesion, sintering and interlocking between ice crystals. Charged cloud particles produced measurable variations in the total induced current pulse on the induction ring. The most influential factors comprised initial temperature, lapse rate and charging mechanism. The ions produced in the chamber may deposit onto larger particles and form dipoles during ice nucleation and growth. The small ion concentration was monitored by the NAIS during these runs. Possible short-term aggregates or alignment of particles were observed in-situ with the SIMONE. These and future chamber measurements of charging and aggregation could shed more light on the ambient conditions and dynamics for electrification in the atmosphere.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.237
Teacher spread0.228 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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