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Record W4404730818 · doi:10.2533/chimia.2024.754

Multiphase Chemistry in the Atmosphere

2024· article· en· W4404730818 on OpenAlexaff
Markus Ammann, Peter A. Alpert, Luca Artiglia, Fengxia Bao, Thorsten Bartels‐Rausch, Juan F. Florez-Ospina, Natasha M. Garner, Lucia Iezzi, Kevin Kilchhofer, Andrés Laso, Luca Longetti, Fabian Mahrt

Bibliographic record

VenueCHIMIA International Journal for Chemistry · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of British Columbia
FundersHORIZON EUROPE Marie Sklodowska-Curie ActionsNational Science FoundationScience Foundation IrelandUniversità degli Studi di PadovaSimons FoundationUniversity of Chinese Academy of SciencesChinese Academy of SciencesSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsAtmospheric chemistryParticulatesAtmosphere (unit)Trace gasChemistrySnowChemical reactionEnvironmental chemistryAerosolChemical physicsChemical processEarth scienceAstrobiologyOzoneMeteorologyGeologyOrganic chemistry

Abstract

fetched live from OpenAlex

Earth's atmosphere comprises a complex mix of gas and condensed phases, where condensed phases facilitate multiphase chemical reactions that would not occur in the gas phase alone. These reactions drive dynamic physical and chemical processes across various spatial and temporal scales, playing a crucial role in the cycling of atmospheric trace constituents. Multiphase chemistry significantly influences geochemical cycles, human health, and climate. This review focuses on the chemical steps governing the cycling of important species, such as halogens, reactive nitrogen, and organics, within aerosol particles, a key type of atmospheric condensed phases, and at condensed phase-air interfaces. These interfaces include mineral oxides, ice, and aqueous solutions found in particulate matter, clouds, snow, and on oceanic and terrestrial surfaces. This review also discusses the important role of redox chemical cycling, the hydrogen bonding network and water activity in these processes.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.267
Teacher spread0.254 · 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 designNot applicable
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

Citations3
Published2024
Admission routes1
Has abstractyes

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