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Record W2088063275 · doi:10.1002/mrc.1453

A relativistic DFT study of one-bond fluorine-X indirect spin–spin coupling tensors

2004· article· en· W2088063275 on OpenAlexaff
Kirk W. Feindel, Roderick E. Wasylishen

Bibliographic record

VenueMagnetic Resonance in Chemistry · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicElectron Spin Resonance Studies
Canadian institutionsUniversity of Alberta
FundersSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsChemistrySpin (aerodynamics)AnisotropyTensor (intrinsic definition)DipoleCoupling constantQuantum chemicalCoupling (piping)FluorineQuantum chemistryMagnetic dipole–dipole interactionComputational chemistryRelativistic quantum chemistryQuantum mechanicsMolecular physicsMoleculeThermodynamicsPhysicsOrganic chemistryGeometry

Abstract

fetched live from OpenAlex

The relativistic zeroth-order regular approximation (ZORA) DFT method was employed to investigate indirect spin-spin coupling tensors involving fluorine, (1)J(X, F). The relative contributions of the mechanisms contributing to (1)J(X, F) are discussed, with special attention paid to the magnitude and origin of the anisotropy in this tensor, DeltaJ. This quantum chemical study demonstrates that, for the systems investigated, the ZORA-DFT method reproduces the magnitude of (1)J(X, F)(iso) and indicates that DeltaJ(X, F) is of the same order of magnitude as (1)J(X, F)(iso). Several examples are provided that demonstrate the importance of considering contributions of DeltaJ to the experimental measurement of effective dipolar coupling constants, R(eff). Given the difficulties with determining DeltaJ experimentally and the promising computational results, we suggest that the quantum chemical calculation of (1)J(X, F) be used as a complementary tool to aid in the analysis of data from NMR experiments designed to measure dipolar coupling constants.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
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 head0.013
GPT teacher head0.269
Teacher spread0.256 · 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 designSimulation or modeling
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

Citations14
Published2004
Admission routes1
Has abstractyes

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