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Record W4404628858 · doi:10.1002/ange.202421258

Development and Applications of an Amide Linchpin Reagent

2024· article· en· W4404628858 on OpenAlexafffund
Bhavana Uppalapati, Maxime A. Aubry, Qiang Wang, Dalia Abdelhamid, Monica A. Gill, André M. Beauchemin

Bibliographic record

VenueAngewandte Chemie · 2024
Typearticle
Languageen
FieldChemistry
TopicSynthetic Organic Chemistry Methods
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsReagentChemistryChemoselectivityAmideElectrophileIsocyanateElectrophilic aminationCombinatorial chemistryAminationFunctional groupReactivity (psychology)Organic chemistryCatalysis

Abstract

fetched live from OpenAlex

Abstract Linchpin reagents are building blocks that can be chemoselectively functionalized to afford products with a common, useful functional group. In this work, we describe the development and validation of the first amide linchpin reagent and demonstrate its use as a doubly electrophilic building block for the synthesis of a variety of amides, including challenging classes. The linchpin reagent was first functionalized via rhodium‐catalyzed electrophilic amination. Selected masked C ‐isocyanate products were then further derivatized with Grignard reagents to produce secondary amides, or tertiary amides if an alkylating agent was added subsequently. The success of this sequence relies on fully controlled reactivity at each electrophilic site, first exploiting the weak N−O bond and then, the ability to form the free isocyanate intermediate in situ. The overall transformation proceeds with high chemoselectivity, demonstrating the ability of this new linchpin reagent to form amides through atypical bond construction. Finally, the potential of this reagent as a more broadly applicable NCO linchpin is demonstrated by the formation of lactams and unsymmetrical ureas.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.167
Threshold uncertainty score0.902

Codex and Gemma teacher scores by category

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)0.0010.000

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 head0.023
GPT teacher head0.290
Teacher spread0.267 · 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

Citations1
Published2024
Admission routes2
Has abstractyes

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