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Record W2127373369 · doi:10.1002/jssc.201300383

Multidimensional <scp>GC</scp> using planar microfluidic devices for the characterization of phenolic antioxidants in fuels

2013· article· en· W2127373369 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 · 2013
Typearticle
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsDow Chemical (Canada)
Fundersnot available
KeywordsMass spectrometryAnalytical Chemistry (journal)ChromatographyMicrofluidicsChemistryAnalyteGas chromatographySpectrometerMaterials scienceNanotechnology

Abstract

fetched live from OpenAlex

A multidimensional gas chromatographic approach using planar microfluidic devices for Deans switching has been developed and implemented for the characterization of sterically hindered phenolic compounds used as antioxidants in fuels. Detection and quantitation was conducted with MS in selected ion monitoring mode. A complete analysis is conducted in less than 15 min with precision greater than 5.5% at 1 and 25 ppm w/w (ppm(w)). LODs of 50 ppb w/w (ppb(w)) or better in selected ion monitoring mode and a linear range of 100 ppb(w) to 100 ppm(w) with a correlation coefficient greater than 0.998 were attained for all analytes. Unique to this analytical configuration is the use of a mass spectrometer capable of monitoring the column effluent from either dimension by incorporating a high-temperature rotary valve and a three-port planar microfluidic device. High-molecular-weight (C25-C40) fuel contaminants eluting from the first column can be selectively sent to the mass spectrometer for profile characterization in scan mode. These compounds would otherwise be retained substantially by the low-phase-ratio analytical column employed in the second dimension.

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)0.000
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 score0.061
Threshold uncertainty score0.208

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.025
GPT teacher head0.289
Teacher spread0.264 · 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