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Record W2318770368 · doi:10.1021/jo501134d

Organoboron-Based Allylation Approach to the Total Synthesis of the Medium-Ring Dilactone (+)-Antimycin A<sub>1b</sub>

2014· article· en· W2318770368 on OpenAlexafffund
John Janetzko, Robert A. Batey

Bibliographic record

VenueThe Journal of Organic Chemistry · 2014
Typearticle
Languageen
FieldChemistry
TopicSynthetic Organic Chemistry Methods
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversities Space Research Association
KeywordsChemistryStereocenterTotal synthesisStereochemistryRing (chemistry)StereoselectivityYield (engineering)HydroborationAmideReagentEnantioselective synthesisOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

The stereoselective synthesis of (+)-antimycin A1b has been accomplished in 12 linear steps and 18% overall yield from (-)-ethyl lactate. A robust, scalable, and highly diastereoselective montmorillonite K10-promoted allylation reaction between an α-silyloxy aldehyde and a substituted potassium allyltrifluoroborate salt provides a general approach to the core stereochemical triad of the antimycin A family. The requisite (Z)-substituted potassium allyltrifluoroborate salt was synthesized using a syn-selective hydroboration/protodeboration of an alkynylboronate ester, followed by a Matteson homologation reaction. The total synthesis leverages an MNBA (Shiina's reagent)-mediated macrolactonization to generate the 9-membered dilactone ring and a late-stage PyBOP-mediated amide coupling employing an unprotected 3-formamidosalicylic acid fragment, thereby shortening the longest linear sequence and, perhaps most notably, generating the antimycin A C7-C8-C9 stereotriad in a single step using a single chiral pool-derived stereocenter.

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)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.010
GPT teacher head0.219
Teacher spread0.209 · 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

Citations20
Published2014
Admission routes2
Has abstractyes

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