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Record W2092436669 · doi:10.3390/molecules20046959

Kinugasa Reactions in Water: From Green Chemistry to Bioorthogonal Labelling

2015· review· en· W2092436669 on OpenAlex
Mariya Chigrinova, Douglas A. MacKenzie, Allison R. Sherratt, Lawrence L. W. Cheung, John Paul Pezacki

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMolecules · 2015
Typereview
Languageen
FieldChemistry
TopicClick Chemistry and Applications
Canadian institutionsUniversity of OttawaNational Research Council Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBioorthogonal chemistryChemistryLabellingAqueous mediumCombinatorial chemistryAqueous solutionGreen chemistryScope (computer science)Organic chemistryReaction mechanismCatalysisClick chemistryComputer scienceBiochemistry

Abstract

fetched live from OpenAlex

The Kinugasa reaction has become an efficient method for the direct synthesis of β-lactams from substituted nitrones and copper(I) acetylides. In recent years, the reaction scope has been expanded to include the use of water as the solvent, and with micelle-promoted [3+2] cycloadditions followed by rearrangement furnishing high yields of β-lactams. The high yields of stable products under aqueous conditions render the modified Kinugasa reaction amenable to metabolic labelling and bioorthogonal applications. Herein, the development of methods for use of the Kinugasa reaction in aqueous media is reviewed, with emphasis on its potential use as a bioorthogonal coupling strategy.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.951
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.064
GPT teacher head0.327
Teacher spread0.263 · 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