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Record W2134366495 · doi:10.1139/v09-100

Experimental and theoretical investigations of selenium nuclear magnetic shielding tensors in Se–N heterocycles

2009· article· en· W2134366495 on OpenAlexaffvenue
Andre Sutrisno, Andy Y. H. Lo, Joel A. Tang, Jason L. Dutton, G.J. Farrar, Paul J. Ragogna, Shaohui Zheng, Jochen Autschbach, Robert W. Schurko

Bibliographic record

VenueCanadian Journal of Chemistry · 2009
Typearticle
Languageen
FieldChemistry
TopicAdvanced NMR Techniques and Applications
Canadian institutionsUniversity of WindsorWestern University
Fundersnot available
KeywordsChemistryIntermolecular forceDensity functional theorySeleniumLone pairComputational chemistryNuclear magnetic resonance spectroscopyElectromagnetic shieldingMolecular orbitalCrystallographyNMR spectra databaseNatural bond orbitalChemical shiftMoleculeSpectral lineStereochemistryPhysical chemistryPhysics

Abstract

fetched live from OpenAlex

A preliminary study involving solid-state 77 Se NMR spectroscopy and first principles calculations of 77 Se NMR parameters in Se–N heterocycles is reported. 77 Se CP/MAS NMR spectra of the ring systems reveal expansive selenium chemical shift (CS) tensors, which are extremely sensitive to molecular geometry, symmetry, ligand substitution, and intermolecular contacts. For systems with known crystal structures, hybrid density functional theory (DFT) calculations of selenium nuclear magnetic shielding (NMS) tensors were carried out, and tensor orientations in the molecular frames examined. Additional DFT calculations of selenium NMS tensors are presented, along with a detailed analysis of pairs of occupied and virtual molecular orbitals that give rise to the Se NMS tensors. A new naturalized local molecular orbital (NLMO) analysis under the same DFT framework is also discussed. Collectively, the NMR data and first principles calculations provide understanding of the influences of electronic structure, bonding, and intermolecular interactions on the selenium NMS tensors, allowing for (i) prediction of unknown molecular structures and (ii) insight into the positions of the stereochemically active selenium lone pairs.

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: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.584

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)0.0010.000

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 head0.009
GPT teacher head0.245
Teacher spread0.235 · 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

Citations14
Published2009
Admission routes2
Has abstractyes

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