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Record W2802941495 · doi:10.1002/cmr.a.21412

Solid‐state nuclear magnetic resonance and nuclear quadrupole resonance as complementary tools to study quadrupolar nuclei in solids

2016· article· en· W2802941495 on OpenAlex
Patrick M. J. Szell, David L. Bryce

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueConcepts in Magnetic Resonance Part A · 2016
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsUniversity of Ottawa
FundersNational Research Council CanadaNatural Sciences and Engineering Research Council of CanadaBruker BioSpinFonds National de la Recherche LuxembourgNational High Magnetic Field LaboratoryUniversity of OttawaNational Science Foundation
KeywordsNuclear quadrupole resonanceElectric field gradientSolid-state nuclear magnetic resonanceNuclear magnetic resonanceQuadrupoleNuclear magnetic resonance spectroscopySpectroscopySolid-stateElectromagnetic shieldingMaterials scienceResonance (particle physics)ChemistryCondensed matter physicsPhysical chemistryPhysicsAtomic physics

Abstract

fetched live from OpenAlex

Abstract Solid‐state nuclear magnetic resonance ( SSNMR ) spectroscopy has largely overtaken nuclear quadrupole resonance ( NQR ) spectroscopy for the study of quadrupolar nuclei. In addition to information on the electric field gradient, SSNMR spectra may offer additional information concerning other NMR interactions such as magnetic shielding. With continued technological advances contributing to developments such as higher magnetic fields, SSNMR boasts several practical advantages over NQR . However, NQR is still a relevant technique, as it may often be the most practical approach in cases of extremely large quadrupolar coupling constants. Here, we discuss the advantages and disadvantages of SSNMR and NQR spectroscopies, with the quadrupolar halogens serving as examples. The purpose of this article is to serve as a guide on using SSNMR and NQR as complementary tools, covering some of their practicalities, limitations, and experimental challenges.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.927
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.327
Teacher spread0.306 · 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