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Record W2161107826 · doi:10.1029/2009gl038727

Ice particle growth in the polar summer mesosphere: Formation time and equilibrium size

2009· article· en· W2161107826 on OpenAlexafffund
A. Y. Zasetsky, S. V. Petelina, R. G. Remorov, C. D. Boone, P. F. Bernath, E. J. Llewellyn

Bibliographic record

VenueGeophysical Research Letters · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsUniversity of SaskatchewanRegional Municipality of WaterlooUniversity of Waterloo
FundersNatural Environment Research CouncilNatural Sciences and Engineering Research Council of CanadaCanadian Space Agency
KeywordsMesospherePolarAtmospheric sciencesWater vaporParticle (ecology)Range (aeronautics)Particle sizePolar nightVolume (thermodynamics)Environmental scienceMaterials sciencePhysicsMeteorologyChemistryStratosphereGeologyThermodynamicsAstronomy

Abstract

fetched live from OpenAlex

The growth kinetics for ice particles in the polar summer mesosphere is studied using the density of water vapor, temperature, and total ice volume simultaneously measured by the infrared Fourier Transform Spectrometer on the Atmospheric Chemistry Experiment (ACE‐FTS) satellite. The results are based solely on the ACE‐FTS retrievals, without using any adjustable parameters. The computed particle formation time is in the range between 2 hours at 150 K and 20 hours at 120 K, during which particles come to equilibrium with water vapor and reach the size of 20–70 nm. The growth rate varies from 0.2 nm/hour to 30 nm/hour in the temperature range analyzed. As it takes ice crystals only 20 minutes to grow by 10 nm at 150 K, the transition from optically subvisible to the visible size range can occur on a time scale of minutes. This could account for fast variations in PMC brightness observed recently.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.684
Threshold uncertainty score1.000

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.024
GPT teacher head0.270
Teacher spread0.246 · 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.

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

Citations19
Published2009
Admission routes2
Has abstractyes

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