MétaCan
Menu
Back to cohort
Record W1991063380 · doi:10.1002/rcm.714

Quantitative determination of polar and ionic compounds in petroleum fractions by atmospheric pressure chemical ionization and electrospray ionization mass spectrometry

2002· article· en· W1991063380 on OpenAlexaff
Stilianos G. Roussis, James W. Fedora

Bibliographic record

VenueRapid Communications in Mass Spectrometry · 2002
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsImperial Oil (Canada)
Fundersnot available
KeywordsAtmospheric-pressure chemical ionizationChemistryAnalyteMass spectrometryElectrospray ionizationChromatographyAnalytical Chemistry (journal)Direct electron ionization liquid chromatography–mass spectrometry interfaceElectrosprayIonizationChemical ionizationIonic bondingDesorption electrospray ionizationIonOrganic chemistry

Abstract

fetched live from OpenAlex

The capabilities of atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI) methods for quantitative analysis of polar and ionic compounds in petroleum fractions have been examined. The requirements of the analysis for sensitivity, linear dynamic range, and structural characterization have been discussed. ESI was found to be approximately two orders of magnitude more sensitive than APCI and is most suitable for the detection of analytes in weak concentrations. Equivalent relative linear dynamic ranges were observed by the two methods (at least three orders of magnitude). For the relatively high analyte concentrations examined here (e.g., 1-100 ppm or higher), the absolute area counts increased linearly with the analyte amount only in APCI, making this method more attractive for quantitative liquid chromatography/mass spectrometry (LC/MS) applications. Nevertheless, a wider range of ionic compounds can be detected by ESI than by APCI.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.265
Teacher spread0.252 · 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

Citations31
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueRapid Communications in Mass SpectrometrySame topicMass Spectrometry Techniques and ApplicationsFrench-language works237,207