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Record W3010470590 · doi:10.3390/molecules25051085

Unveiling the Different Chemical Reactivity of Diphenyl Nitrilimine and Phenyl Nitrile Oxide in [3+2] Cycloaddition Reactions with (R)-Carvone through the Molecular Electron Density Theory

2020· article· en· W3010470590 on OpenAlexaff
Mar Ríos‐Gutiérrez, Luís R. Domingo, M. Esseffar, Ali Oubella, My Youssef Ait Itto

Bibliographic record

VenueMolecules · 2020
Typearticle
Languageen
FieldChemistry
TopicOrganic Chemistry Cycloaddition Reactions
Canadian institutionsMcMaster University
FundersH2020 Marie Skłodowska-Curie ActionsMinisterio de Economía y CompetitividadEuropean Commission
KeywordsCycloadditionNitrileDensity functional theoryReactivity (psychology)CarbenoidChemistryFukui functionComputational chemistryMedicinal chemistryOrganic chemistryElectrophileCatalysis

Abstract

fetched live from OpenAlex

The [3+2] cycloaddition (32CA) reactions of diphenyl nitrilimine and phenyl nitrile oxide with (R)-carvone have been studied within the Molecular Electron Density Theory (MEDT). Electron localisation function (ELF) analysis of these three-atom-components (TACs) permits its characterisation as carbenoid and zwitterionic TACs, thus having a different reactivity. The analysis of the conceptual Density Functional Theory (DFT) indices accounts for the very low polar character of these 32CA reactions, while analysis of the DFT energies accounts for the opposite chemoselectivity experimentally observed. Topological analysis of the ELF along the single bond formation makes it possible to characterise the mechanisms of these 32CA reactions as cb- and zw-type. The present MEDT study supports the proposed classification of 32CA reactions into pdr-, pmr-, cb- and zw-type, thus asserting MEDT as the theory able to explain chemical reactivity in Organic Chemistry.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.007
GPT teacher head0.203
Teacher spread0.196 · 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 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

Citations40
Published2020
Admission routes1
Has abstractyes

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