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Record W3012056793 · doi:10.1002/9780470027318.a9655

The Recent Development and Application of Chemical Ionization Mass Spectrometry in Atmospheric Chemistry

2018· other· en· W3012056793 on OpenAlex
Ran Zhao

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEncyclopedia of Analytical Chemistry · 2018
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsChemistryMass spectrometryChemical ionizationIonDirect electron ionization liquid chromatography–mass spectrometry interfaceIonizationAtmospheric-pressure chemical ionizationReagentAnalyteElectron ionizationMass spectrumMoleculeIon sourceAnalytical Chemistry (journal)Desorption electrospray ionizationOrganic chemistryChromatography

Abstract

fetched live from OpenAlex

Abstract Chemical ionization mass spectrometry (CIMS) is a soft ionization mass spectrometric technique. Instead of electron impaction, analytes are ionized by a reagent ion via ion–molecule reactions, such as proton transfer, charge transfer, and ion–analyte cluster formation. The product ions tend to retain the mass of the analytes, making CIMS an ideal technique to provide molecular‐level chemical information. This feature of CIMS brings significant advantages to the research field of atmospheric chemistry. This article highlights the development and application of CIMS in atmospheric chemistry over the past decade, with a focus on instrumental development and underlying ion–molecule reactions of commonly employed reagent ions.

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.

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: Other · Consensus signal: Other
Teacher disagreement score0.625
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 science0.0000.000
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 head0.005
GPT teacher head0.202
Teacher spread0.197 · 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