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Record W2316992653 · doi:10.1021/jf5049595

Characterization of Phospholipids by Two-Dimensional Liquid Chromatography Coupled to In-line Ozonolysis–Mass Spectrometry

2015· article· en· W2316992653 on OpenAlexafffund
Chenxing Sun, Yuanyuan Zhao, Jonathan M. Curtis

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2015
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsAlberta Ministry of Agriculture and ForestryUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOzonolysisChemistryMass spectrometryChromatographyDouble bondHydrophilic interaction chromatographyMoleculeOzoneLiquid chromatography–mass spectrometryCharacterization (materials science)Analytical Chemistry (journal)High-performance liquid chromatographyOrganic chemistryMaterials scienceNanotechnology

Abstract

fetched live from OpenAlex

In this study, the characterization of phospholipids (PL) was achieved by using a combination of LC/MS/MS and two-dimensional LC/MS. A HILIC LC column was used for PL class separation, while the further molecular species separation of each PL class was achieved by using online HILIC × C18 LC. The double bond positions along the fatty acyl chains of these PL molecular species were also obtained by using the combination of 2D-LC and in-line ozonolysis-MS analysis. The ozonolysis device is composed of a gas-permeable, liquid-impermeable Teflon tube passing through a glass chamber filled with ozone gas, which is then placed in-line between the 2D-LC and the mass spectrometer. The eluting PL molecules in the LC mobile phase passed through the device where they rapidly reacted with the ozone that penetrated through the tubing wall. The ozonolysis products were then detected by MS in real-time, which allowed the localization of the double bonds along the fatty acyl chains in these PL molecular species. This comprehensive method was successfully applied to an egg yolk PL extract, which revealed the detailed structures of the PL molecules.

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 score0.001
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.008
GPT teacher head0.208
Teacher spread0.200 · 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

Citations25
Published2015
Admission routes2
Has abstractyes

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