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Record W1945144029 · doi:10.1002/rcm.5063

Carbon disulfide reagent allows the characterization of nonpolar analytes by atmospheric pressure chemical ionization mass spectrometry

2011· article· en· W1945144029 on OpenAlexaff
Jinshan Gao, David J. Borton, Lucas M. Amundson, Enada F. Archibold, Xiaoli Tan, Khalid Azyat, Rik R. Tykwinski, Murray R. Gray, Hilkka I. Kenttämaa

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2011
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of SaskatchewanUniversity of Alberta
Fundersnot available
KeywordsChemistryAtmospheric-pressure chemical ionizationMass spectrometryReagentChemical ionizationAtmospheric pressureAnalyteChromatographyOrganic chemistryAnalytical Chemistry (journal)IonizationIon

Abstract

fetched live from OpenAlex

While atmospheric pressure ionization methodologies have revolutionized the mass spectrometric analysis of nonvolatile analytes, limitations native to the chemistry of these methodologies hinder or entirely inhibit the analysis of certain analytes, specifically, many nonpolar compounds. Examination of various analytes, including asphaltene and lignin model compounds as well as saturated hydrocarbons, demonstrates that atmospheric pressure chemical ionization (APCI) using CS(2) as the reagent produces an abundant and stable molecular ion (M(+•)) for all model compounds studied, with the exception of completely saturated aliphatic hydrocarbons and the two amino acids tested, arginine and phenylalanine. This reagent substantially broadens the applicability of mass spectrometry to nonvolatile nonpolar analytes and also facilitates the examination of radical cation chemistry by mass spectrometry.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.154
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.242
Teacher spread0.227 · 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 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

Citations35
Published2011
Admission routes1
Has abstractyes

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