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Record W2329047858 · doi:10.1021/jf4045638

Comprehensive Multiphase NMR Spectroscopy of Intact <sup>13</sup>C-Labeled Seeds

2013· article· en· W2329047858 on OpenAlexaff
Leayen Lam, Ronald Soong, Andre Sutrisno, Ries de Visser, Myrna J. Simpson, Heather L. Wheeler, Malcolm M. Campbell, Werner Maas, Michael Fey, A. Gorissen, Howard Hutchins, Brian Andrew, Jochem Struppe, Sridevi Krishnamurthy, Rajeev Kumar, Martine Monette, Henry J. Stronks, Alan Hume, André J. Simpson

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2013
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsThe Scarborough HospitalBruker (Canada)University of Toronto
Fundersnot available
KeywordsEndospermNuclear magnetic resonance spectroscopyChemistrySpectroscopySolid-state nuclear magnetic resonancePhase (matter)Isotopic labelingChromatographyAnalytical Chemistry (journal)Organic chemistryBiochemistryNuclear magnetic resonance

Abstract

fetched live from OpenAlex

Seeds are complex entities composed of liquids, gels, and solids. NMR spectroscopy is a powerful tool for studying molecular structure but has evolved into two fields, solution and solid state. Comprehensive multiphase (CMP) NMR spectroscopy is capable of liquid-, gel-, and solid-state experiments for studying intact samples where all organic components are studied and differentiated in situ. Herein, intact (13)C-labeled seeds were studied by a variety of 1D/2D (1)H/(13)C experiments. In the mobile phase, an assortment of metabolites in a single (13)C-labeled wheat seed were identified; the gel phase was dominated by triacylglycerides; the semisolid phase was composed largely of carbohydrate biopolymers, and the solid phase was greatly influenced by starchy endosperm signals. Subsequently, the seeds were compared and relative similarities and differences between seed types discussed. This study represents the first application of CMP-NMR to food chemistry and demonstrates its general utility and feasibility for studying intact heterogeneous samples.

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 score0.014
Threshold uncertainty score0.448

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 communication0.0000.000
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 head0.012
GPT teacher head0.219
Teacher spread0.208 · 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

Citations41
Published2013
Admission routes1
Has abstractyes

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