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Record W2002909676 · doi:10.1002/poc.1398

Thermodynamics of competing oxidation reactions of allyl methyl disulfide by hydrogen peroxide: a first principle molecular computational study on the conformations of allyl methyl disulfide and its oxidized products

2008· article· en· W2002909676 on OpenAlexaff
Matías F. Andrada, Juan C. Garro Martínez, Milán Szöri, Graciela N. Zamarbide, Francisco Tomás Vert, Béla Viskolcz, Mario R. Estrada, Imre G. Csizmadia

Bibliographic record

VenueJournal of Physical Organic Chemistry · 2008
Typearticle
Languageen
FieldChemistry
TopicFree Radicals and Antioxidants
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChemistryDisulfide bondSulfoxideEpoxideHydrogen peroxidePeroxideEquilibrium constantComputational chemistryMedicinal chemistryDensity functional theoryPhotochemistryOrganic chemistryPhysical chemistryCatalysis

Abstract

fetched live from OpenAlex

Abstract Allyl methyl disulfide, a peroxide scavenger, was studied together with three isomeric (two sulfoxides and one epoxide) forms of its mono‐oxidized products. After a full conformational study of the reactant and three isomeric oxidized forms, the geometries were optimized at B3LYP/6‐31G (d) level of theory. The epoxide form turned and to be more stable than either one of the two isomeric sulfoxides. Changes for Thermodynamic functions of oxidation reactions were calculated and from the δGreaction values the equilibrium constant for the interconversions of the oxidized products were estimated. Bader‐type AIM analyses were performed on the electron density, computed at the B3LYP/6‐311++G (d,p) level of theory. In several of the sulfoxide conformations CH···OS< secondary interactions were observed. Copyright © 2008 John Wiley & Sons, Ltd.

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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.246
Teacher spread0.233 · 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

Citations6
Published2008
Admission routes1
Has abstractyes

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