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Acquisition of Wideline Solid-State NMR Spectra of Quadrupolar Nuclei

2011· reference-entry· en· W1481682663 on OpenAlexaff
Robert W. Schurko

Bibliographic record

VenueEncyclopedia of Magnetic Resonance · 2011
Typereference-entry
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsSpectral lineNMR spectra databaseSolid-state nuclear magnetic resonanceNuclear magnetic resonance spectroscopyNuclear magnetic resonanceExcitationSolid-stateCarbon-13 NMR satelliteMaterials scienceAnalytical Chemistry (journal)ChemistryPhysicsEngineering physics

Abstract

fetched live from OpenAlex

Solid-state NMR is increasingly used for the study of quadrupolar nuclei (spin > 1/2) across the periodic table. There are numerous instances where the magnitude of the quadrupolar interaction is so great that the NMR powder patterns span ranges of hundreds of kilohertz to tens of megahertz, well beyond the range of conventional wideline patterns. Such spectra, which we refer to as ultra-wideline (UW) NMR spectra, cannot be acquired using standard high-power, rectangular pulses, since the associated excitation bandwidths are often much smaller than the pattern breadths. However, it is possible to acquire high-quality UW NMR spectra utilizing a combination of frequency-stepped spectral acquisitions, CPMG echo trains, and chirped pulses. The use of probes with large detection bandwidths and high magnetic fields also greatly aid in improving spectral quality. In this article, techniques for the acquisition of UW NMR spectra are discussed, along with hardware considerations and examples of applications of UW NMR to a variety of materials.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.009

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 head0.013
GPT teacher head0.268
Teacher spread0.255 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations36
Published2011
Admission routes1
Has abstractyes

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