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Record W4308592565 · doi:10.26434/chemrxiv-2022-4ljh2

Detection of Pyridine Derivatives by SABRE Hyperpolarization at Zero Field

2022· preprint· en· W4308592565 on OpenAlexaff
Piotr Put, Şeyma Alçiçek, Oksana Bondar, Łukasz Bodek, Simon B. Duckett, Szymon Pustelny

Bibliographic record

VenueChemRxiv · 2022
Typepreprint
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsYork University
FundersEuropean Commission
KeywordsHyperpolarization (physics)Spin isomers of hydrogenChemistryInduced polarizationAmplitudePolarization (electrochemistry)Nuclear magnetic resonance spectroscopyNuclear magnetic resonanceChemical physicsPhysicsPhysical chemistryStereochemistryOrganic chemistryQuantum mechanicsHydrogen

Abstract

fetched live from OpenAlex

Zero-field nuclear magnetic resonance (NMR) recently emerged as an interesting new analytical modality. While zero-field NMR provides new capabilities, it also suffers from some limitations associated, to a great degree, with low signal amplitude. In this context, parahydrogen-induced polarization naturally complements zero-field NMR, as this hyperpolarization is active even at zero magnetic field. In turn, the efficient production of large non-equilibrium polarization is possible in zero field, boosting the signal amplitude and enabling realization of the concept of "NMR without magnets''. In this work, we present zero-field NMR studies of various hyperpolarized pyridine derivatives where the 15N isotope is present at a natural abundance (0.36%). By comparing the signals of these pyridine derivatives, which include vitamin B3, as a function of their substituents, we demonstrate unique zero-field NMR spectra, consequently establishing how chemical analysis is possible even in zero field. We also study the effect of the parahydrogen-polarization-transfer catalyst activation on the resulting hyperpolarization dynamics. All of these measurements were made using apparatus designed to allow repeated in situ hyperpolarization of these samples without affecting their composition.

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 categoriesInsufficient payload (model declined to judge)
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 score0.110
Threshold uncertainty score0.999

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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.272
Teacher spread0.258 · 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.

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

Citations4
Published2022
Admission routes1
Has abstractyes

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