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Record W4295424681 · doi:10.1007/s00216-022-04292-0

Site-specific carbon isotope measurements of vanillin reference materials by nuclear magnetic resonance spectrometry

2022· article· en· W4295424681 on OpenAlexafffund
Phuong Mai Le, Estelle Martineau, Serge Akoka, Gérald S. Remaud, Michelle M. G. Chartrand, Juris Meija, Zoltán Mester

Bibliographic record

VenueAnalytical and Bioanalytical Chemistry · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBiochemical and biochemical processes
Canadian institutionsMétis National CouncilNational Research Council Canada
FundersNational Research Council CanadaAgence Nationale de la Recherche
KeywordsVanillinMass spectrometryChemistryIsotopeCarbon fibersIsotope-ratio mass spectrometryIsotopes of carbonIsotopic ratioAnalytical Chemistry (journal)Detection limitEnvironmental chemistryChromatographyTotal organic carbonOrganic chemistryMaterials scienceNuclear physicsPhysics

Abstract

fetched live from OpenAlex

Abstract Vanillin, one of the world’s most popular flavor used in food and pharmaceutical industries, is extracted from vanilla beans or obtained (bio)-synthetically. The price of natural vanillin is considerably higher than that of its synthetic alternative which leads increasingly to counterfeit vanillin. Here, we describe the workflow of combining carbon isotope ratio combustion mass spectrometry with quantitative carbon nuclear magnetic resonance spectrometry ( 13 C-qNMR) to obtain carbon isotope measurements traceable to the Vienna Peedee Belemnite (VPDB) with 0.7‰ combined standard uncertainty (or expanded uncertainty of 1.4‰ at 95% confidence level). We perform these measurements on qualified Bruker 400 MHz instruments to certify site-specific carbon isotope delta values in two vanillin materials, VANA-1 and VANB-1, believed to be the first intramolecular isotopic certified reference material (CRMs). Graphical abstract

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.016
GPT teacher head0.221
Teacher spread0.205 · 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 source (direct Gemma or distilled Codex), 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

Citations14
Published2022
Admission routes2
Has abstractyes

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