MétaCan
Menu
Back to cohort
Record W2078295226 · doi:10.1021/ef000225v

Hydrocarbon Compound Type Analysis by Mass Spectrometry:  On the Replacement of the All-Glass Heated Inlet System with a Gas Chromatograph

2001· article· en· W2078295226 on OpenAlexaff
Stilianos G. Roussis, W. Pat Fitzgerald

Bibliographic record

VenueEnergy & Fuels · 2001
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsImperial Oil (Canada)
Fundersnot available
KeywordsMass spectrometryChemistryRepeatabilityGas chromatographyChromatographyAnalytical Chemistry (journal)HydrocarbonGas chromatography–mass spectrometryHydrocarbon mixturesSample preparationOrganic chemistry

Abstract

fetched live from OpenAlex

Hydrocarbon compound type analysis by mass spectrometry is a simple and powerful method that provides extensive compositional information about complex petroleum fractions. Sample introduction into the mass spectrometer has been successfully done for over 30 years using the all-glass heated inlet system (AGHIS). However, the limited transportability of the AGHIS has considerably restricted the wider usage of mass spectrometry for hydrocarbon compound type analysis. In this work, a gas chromatograph (GC) has been examined as a system equivalent to the AGHIS for the introduction of petroleum fractions into the mass spectrometer (MS). It is demonstrated that the GC is a versatile system that offers many advantages over the AGHIS, including simplicity of operation, ease of maintenance, automation, and transportability. Most importantly, the use of the GC allows for the detection of individual compounds, a feature not available with the AGHIS. The capabilities of the GC/MS system have been examined by the analysis of several representative petroleum fractions. The differences in the results obtained by the two sample introduction methods are of the same order of magnitude as the repeatability of the two methods. The ability of the GC/MS system to determine individual compounds in low-boiling-range samples has been illustrated by the use of selective-ion monitoring (SIM) experiments. Individual compounds in heavier samples have been determined by using the automated deconvolution program AMDIS to separate overlapping components.

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 score0.055
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

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

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 head0.007
GPT teacher head0.202
Teacher spread0.194 · 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

Citations12
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueEnergy & FuelsSame topicAnalytical Chemistry and ChromatographyFrench-language works237,207