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Record W2164130039 · doi:10.1039/c4sc02026j

Mechanistic insights into hydroacylation with non-chelating aldehydes

2014· article· en· W2164130039 on OpenAlexaff
Stephen K. Murphy, Achim Bruch, Vy M. Dong

Bibliographic record

VenueChemical Science · 2014
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicChemical Reactions and Isotopes
Canadian institutionsUniversity of Toronto
FundersNational Institute of General Medical SciencesNational Institutes of HealthDeutscher Akademischer Austauschdienst
KeywordsHydroacylationChelationChemistryCombinatorial chemistryComputer scienceAldehydeOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

catalyses the hydroacylation of 2-vinylphenols with a wide range of non-chelating aldehydes. Here we present a detailed experimental study that elucidates the factors contributing to the broad aldehyde scope and high reactivity. A variety of catalytically relevant intermediates were isolated and a [Rh(dcpm)(vinylphenolate)] complex was identified as the major catalytically relevant species. A variety of off-cycle intermediates were also identified that can re-enter the catalytic cycle by substrate- or 1,5-cyclooctadiene-mediated pathways. Saturation kinetics with respect to the 2-vinylphenol were observed, and this may contribute to the high selectivity for hydroacylation over aldehyde decarbonylation. A series of deuterium labelling experiments and Hammett studies support the oxidative addition of Rh to the aldehyde C-H bond as an irreversible and turnover-limiting step. The small bite angle of dcpm is crucial for lowering the barrier of this step and providing excellent reactivity with a variety of aldehydes.

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 score0.002
Threshold uncertainty score0.008

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.045
GPT teacher head0.389
Teacher spread0.344 · 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

Citations59
Published2014
Admission routes1
Has abstractyes

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