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Record W2006488168 · doi:10.1002/ejoc.201001596

Easy Routes towards Chiral Lithium Binaphthylamido Catalysts for the Asymmetric Hydroamination of Amino‐1,3‐dienes and Aminoalkenes

2011· article· en· W2006488168 on OpenAlexfundno aff
Julia Deschamp, Jacqueline Collin, Jérôme Hannedouche, Emmanuelle Schulz

Bibliographic record

VenueEuropean Journal of Organic Chemistry · 2011
Typearticle
Languageen
FieldChemistry
TopicAsymmetric Hydrogenation and Catalysis
Canadian institutionsnot available
FundersMinistère de l'Education Nationale, de l'Enseignement Supérieur et de la RechercheCentre National de la Recherche ScientifiqueMinistère de l'Enseignement Supérieur et de la RechercheAlberta Innovates - Health Solutions
KeywordsHydroaminationChemistryPiperidineLithium (medication)CatalysisTrimethylsilylPyrrolidineLigand (biochemistry)In situOrganic chemistryOrganic baseCombinatorial chemistryReceptor

Abstract

fetched live from OpenAlex

Abstract The preparation of chiral lithium salts of N , N′ ‐disubstituted binaphthyldiamines and their use as catalysts for asymmetric hydroamination/cyclisation of amino‐1,3‐dienes and aminoalkenes are reported. Several straightforward methods involving the combination of ligand with solutions of methyl‐ or [(trimethylsilyl)methyl]lithium (LiCH 2 TMS) by ex situ or in situ preparation have been investigated. The use of LiCH 2 TMS in an in situ procedure was revealed as theeasiest for carrying out reactions with reliable results by fine‐tuning the quantity of base. Screening of a variety of ligands led to the selection of binaphthyldiamines modified by benzyl, pyridyl or naphthyl groups for the cyclisation of conjugated aminodienes in pyrrolidine or piperidine with the highest stereo‐ and enantioselectivities described to date (up to 61 and 72 % ee , respectively). Primary and secondaryaminoalkenes are efficiently cyclised at room temperature, but with poor enantioselectivities.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.240
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.213
Teacher spread0.195 · 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 teacher head, 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

Citations39
Published2011
Admission routes1
Has abstractyes

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