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Record W2945082191 · doi:10.1039/c9cs00191c

Boronic acid catalysis

2019· review· en· W2945082191 on OpenAlexafffund
Dennis G. Hall

Bibliographic record

VenueChemical Society Reviews · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical Synthesis and Analysis
Canadian institutionsAlberta Hospital EdmontonUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsBoronic acidCatalysisChemistryCombinatorial chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Although boronic acids are recognized primarily for their utility as reagents in transition metal-catalyzed transformations, other applications are emerging, including their use as reaction catalysts. Few methods are available for the catalytic activation of hydroxy functional groups as a way to promote their direct transformation into useful products under mild conditions. To this end, the ability of boronic acids to form reversible covalent bonds with hydroxy groups can be exploited to enable both electrophilic and nucleophilic modes of activation in various organic reactions. Using the concept of boronic acid catalysis (BAC), electrophilic activation of carboxylic acids leads to the formation of amides from amines, as well as cycloadditions and conjugate additions with unsaturated carboxylic acids. Alcohols can also be activated with boronic acid catalysts to form carbocation intermediates that can be trapped in selective Friedel-Crafts-type reactions with arenes and other nucleophiles. On the other hand, diols and saccharides can form tetrahedral adducts with boronic acids, which increases their nucleophilic character towards electrophiles. Altogether, BAC imparts mild and selective reaction conditions that display high atom-economy by circumventing the need for wasteful stoichiometric activation of hydroxy groups into halides or sulfonates.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.004

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 head0.050
GPT teacher head0.331
Teacher spread0.282 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations273
Published2019
Admission routes2
Has abstractyes

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