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Record W1992523757 · doi:10.1021/jo902426z

Unique Diastereoselectivity Trends in Aminyl Radical Cyclizations onto Silyl Enol Ethers

2009· article· en· W1992523757 on OpenAlexaff
María Zlotorzynska, Huimin Zhai, Glenn M. Sammis

Bibliographic record

VenueThe Journal of Organic Chemistry · 2009
Typearticle
Languageen
FieldChemistry
TopicRadical Photochemical Reactions
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChemistrySilylationSteric effectsEnolSilyl enol etherOlefin fiberAlkylArylEnol etherSilyl etherEtherMedicinal chemistryOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

The cyclization of nitrogen-centered radicals onto silyl enol ethers is an efficient method for the synthesis of polyhydroxylated alkaloids as the 2-hydroxymethylpyrrolidine core can be readily accessed from a linear precursor. During our studies on the synthesis of polyhydroxylated alkaloid CYB-3, we found that the diastereoselectivity of the cyclization was dependent on a complex combination of sterics and olefin geometry. A more thorough understanding of the factors that lead to high diastereoselectivites would greatly expand the utility of this methodology in complex natural product synthesis. We have found that cyclization diastereoselectivities of substrates with alkyl or aryl substitution were excellent regardless of olefin geometry or substitution pattern. When electronegative substituents were introduced adjacent to the silyl enol ether, only Z-silyl enol ethers provide high diastereoselectivites. Temperature, steric size of the silyl group, and sterics and electronics of the metal hydride affected the selectivity to a lesser extent.

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 score0.006

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)0.0020.001

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 head0.009
GPT teacher head0.255
Teacher spread0.245 · 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

Citations14
Published2009
Admission routes1
Has abstractyes

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