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Record W1884106930 · doi:10.1002/jssc.201400727

A multidimensional gas chromatography method for the analysis of hydrogen sulfide in crude oil and crude oil headspace

2014· article· en· W1884106930 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Separation Science · 2014
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsNatural Resources Canada
Fundersnot available
KeywordsHydrogen sulfideChemistryGas chromatographySulfurChromatographySulfideChemiluminescenceHydrogenAcid gasCarbonyl sulfideInorganic chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Two-dimensional heart-cutting gas chromatography is used to analyze dissolved hydrogen sulfide in crude samples. Liquid samples are separated first on an HP-PONA column, and the light sulfur gases are heart-cut to a GasPro column, where hydrogen sulfide is separated from other light sulfur gases and detected with a sulfur chemiluminescence detector. Heart-cutting is accomplished with the use of a Deans switch. Backflushing the columns after hydrogen sulfide detection eliminates any problems caused by high-boiling hydrocarbons in the samples. Dissolved hydrogen sulfide is quantified in 14 crude oil samples, and the results are shown in this work. The method is also applicable to the analysis of headspace hydrogen sulfide over crude oil samples. Gas hydrogen sulfide measurements are compared to liquid hydrogen sulfide measurements for the same sample set. The chromatographic system design is discussed, and chromatograms of representative gas and liquid measurements are shown.

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.

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)0.002
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 score0.192
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0000.000
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 head0.015
GPT teacher head0.328
Teacher spread0.313 · 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