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Record W1989654121 · doi:10.1063/1.1689633

Quantum capping potentials with point charges: A simple QM/MM approach for the calculation of large-molecule NMR shielding tensors

2004· article· en· W1989654121 on OpenAlexaff
Seongho Moon, Phillip A. Christiansen, Gino A. DiLabio

Bibliographic record

VenueThe Journal of Chemical Physics · 2004
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsNational Institute for NanotechnologyUniversité de Montréal
Fundersnot available
KeywordsIsotropyElectromagnetic shieldingSimple (philosophy)ChemistryQuantumQM/MMComputational chemistryMoleculePoint particleChromophoreQuantum mechanicsMolecular orbitalMolecular physicsPhysics

Abstract

fetched live from OpenAlex

A simple quantum-mechanics/molecular-mechanics (QM/MM) approach for calculating NMR shielding tensors (sigma) is presented. The method involves capping the QM region with quantum capping potentials (QCPs) and representing the MM region with point charges. Test calculations on simple systems without MM charges show that calculated sigma values improve relative to the full QM results with increasing distance between the capped bond and chromophore. Calculations on the histidine amino acid and cytosine monophosphate (CMP) nucleic acid show that the use of QCPs with point charges result in mean errors in the isotropic component of sigma that are less than 1.6 ppm. The results also reveal that, contrary to previous work, the explicit effect of point charges on sigma through coupling with gauge factors, as in the gauge including atomic orbital approach, is minimal for the CMP molecule. The present QM/MM approach for calculating sigma is easy to apply and requires no code modification.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.655
Threshold uncertainty score0.272

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.287
Teacher spread0.266 · 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 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

Citations21
Published2004
Admission routes1
Has abstractyes

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