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Record W2050481313 · doi:10.1016/j.jasms.2007.01.014

Mobility resolution and mass analysis of ions from ammonia and hydrazine complexes with ketones formed in air at ambient pressure

2007· article· en· W2050481313 on OpenAlexaff
H. R. Bollan, J. A. Stone, J. L. Brokenshire, Jaime E. Rodriguez, Gary A. Eiceman

Bibliographic record

VenueJournal of the American Society for Mass Spectrometry · 2007
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsQueen's University
Fundersnot available
KeywordsChemistryProtonationKetoneMass spectrometryIonIon-mobility spectrometryMoleculeAmmoniaInorganic chemistryAnalytical Chemistry (journal)Organic chemistryChromatography

Abstract

fetched live from OpenAlex

Protonated ammonia and hydrazines (MH(+)) form complexes with ketones and the differences in masses and mobilities of the resulting ions, MH(+)(ketone)(n), are sufficient for separation in an ion mobility spectrometer at ambient pressure. The highest mass ion for any of the protonated molecules is obtained when the ketone is present at elevated concentrations in the supporting atmosphere of both the source and drift regions of the spectrometer so that an ion maintains a discrete composition and mobility. The sizes of the ion-molecule complexes were found to depend on the number of H atoms on the protonated nitrogen atom--four for ammonia, three for hydrazine, two for monomethylhydrazine, and one for 1,1-dimethylhydrazine, and the drift times of these ions were proportional to the size of the ion-molecule complex. Unexpected side products, including protonated hydrazones and azines, and associated ketone clusters, were isolated to a single drift tube containing ceramic parts and could not, from CID studies, be attributed to gas-phase ion chemistry. These findings illustrate that mobility resolution of ions in IMS and IMS/MS experiments can be enhanced through chemical modification of the supporting gas atmosphere without changes in the core ion.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.569
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.263
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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations34
Published2007
Admission routes1
Has abstractyes

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