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Record W2045585102 · doi:10.5194/acp-13-9745-2013

Contact freezing: a review of experimental studies

2013· review· en· W2045585102 on OpenAlexaff
Luis A. Ladino, O. Stetzer, Ulrike Lohmann

Bibliographic record

VenueAtmospheric chemistry and physics · 2013
Typereview
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsUniversity of Toronto
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsIce nucleusIce formationIce crystalsNucleationFreezing behaviorCongelationChemistryMeteorologyThermodynamicsAtmospheric sciencesGeologyPhysics

Abstract

fetched live from OpenAlex

Abstract. This manuscript compiles both theoretical and experimental information on contact freezing with the aim to better understand this potentially important but still not well quantified heterogeneous freezing mode. There is no complete theory that describes contact freezing and how the energy barrier has to be overcome to nucleate an ice crystal by contact freezing. Experiments on contact freezing conducted using the cold plate technique indicate that it can initiate ice formation at warmer temperatures than immersion freezing. Additionally, a qualitative difference in the freezing temperatures between contact and immersion freezing has been found using different instrumentation and different ice nuclei. There is a lack of data on collision rates in most of the reported data, which inhibits a quantitative calculation of the freezing efficiencies. Thus, new or modified instrumentation to study contact nucleation in the laboratory and in the field are needed to identify the conditions at which contact nucleation could occur in the atmosphere. Important questions concerning contact freezing and its potential role for ice cloud formation and climate are also summarized.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.003

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 head0.302
Teacher spread0.266 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations118
Published2013
Admission routes1
Has abstractyes

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