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Record W2092394180 · doi:10.1016/j.jasms.2005.09.013

Factors affecting primary ionization in dopant-assisted atmospheric pressure photoionization (DA-APPI) for LC/MS

2006· article· en· W2092394180 on OpenAlexafffund
Damon B. Robb, Michael W. Blades

Bibliographic record

VenueJournal of the American Society for Mass Spectrometry · 2006
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British Columbia
KeywordsChemistryPhotoionizationDopantIonizationAnalytical Chemistry (journal)SolventQuenching (fluorescence)Excited stateIonPhotochemistryAtomic physicsOrganic chemistryDopingMaterials scienceOptoelectronics

Abstract

fetched live from OpenAlex

The sensitivity of dopant-assisted atmospheric pressure photoionization (DA-APPI) for LC/MS is generally reduced at higher solvent flow rates. Theory suggests that quenching of excited-state precursors to the dopant ions, via collisions with vaporized solvent molecules, may be one mechanism responsible for this trend. To ascertain if the primary rate of ionization is affected by quenching, experiments were performed utilizing an ionization detector to determine the primary ion current generated by irradiating vaporized mixtures of toluene dopant and methanol solvent. The results indicate that no loss of primary ion current occurs as the solvent flow is increased, provided the dopant-to-solvent ratio is held constant. Additional primary ion current can always be generated by increasing the dopant flow rate and/or the lamp power. Thus, quenching of excited-state precursors to the dopant ions, leading to a reduction in the primary rate of ionization, is not the mechanism responsible for the observed loss of sensitivity at higher liquid solvent flow rates.

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 categoriesnone
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 score0.363
Threshold uncertainty score0.888

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.255
Teacher spread0.243 · 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 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

Citations53
Published2006
Admission routes2
Has abstractyes

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