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Record W4285500052 · doi:10.1016/j.jmro.2022.100065

Revisiting dipolar relaxation of a homonuclear spin pair in the presence of a radio frequency field: A tutorial

2022· article· en· W4285500052 on OpenAlexaff
Yuki Toyama

Bibliographic record

VenueJournal of Magnetic Resonance Open · 2022
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHomonuclear moleculeRelaxation (psychology)SpinsZeeman effectField (mathematics)DipoleSpin (aerodynamics)Statistical physicsPhysicsTheoretical physicsComputer scienceMagnetic fieldQuantum mechanicsMathematicsCondensed matter physicsThermodynamicsMoleculePure mathematics

Abstract

fetched live from OpenAlex

NMR studies exploit spin relaxation in a multitude of different ways, providing information on molecular structure and dynamics. Calculating the relaxation rates of NMR active nuclei in multi-spin systems is often a prerequisite for the proper analysis of experimental data. For many researchers the calculations appear complex, often involving different basis sets or expressions describing relaxation in different frames. In this tutorial paper we derive expressions for dipolar relaxation of an I-S two spin spin-system in the presence of a B1 radio frequency field, where spins I and S can be either like or unlike. We consider two different approaches for the derivation of relaxation elements that have been used in the literature, including one where a series of transformations are carried out to the interaction representation of the effective field, comprising B1 and Zeeman components. A second procedure is based on the well-known Solomon equations. We show that both approaches lead to identical results, in the process presenting a pedagogical description of relaxation theory.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.015
GPT teacher head0.293
Teacher spread0.277 · 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 designNot applicable
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

Citations1
Published2022
Admission routes1
Has abstractyes

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