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Record W1548262875 · doi:10.1002/9783527678174.ch08

Metal‐Catalyzed Multicomponent Synthesis of Heterocycles

2014· other· en· W1548262875 on OpenAlexaff
Fabio Lorenzini, Jevgenijs Tjutrins, Jeffrey S. Quesnel, Bruce A. Arndtsen

Bibliographic record

Venuenot available
Typeother
Languageen
FieldChemistry
TopicCatalytic C–H Functionalization Methods
Canadian institutionsMcGill University
Fundersnot available
KeywordsCycloadditionCatalysisChemistryAlkyneCoupling reactionPalladiumCombinatorial chemistryHeteroatomMetallacycleTransition metalRing (chemistry)Organic chemistry

Abstract

fetched live from OpenAlex

Transition metal-catalyzed multicomponent coupling reactions (MCRs) have been developed using a variety of reaction platforms. This chapter focuses on general variants of these reactions that target heterocyclic products. It highlights catalytic transformations that lead to three or more bonds from available and tunable substrates, as these can provide routes to rapidly assemble complex heterocyclic products in an efficient fashion. A common platform exploited in metal-catalyzed multicomponent coupling reactions involves palladium-catalyzed cross-coupling, Heck coupling, or related catalytic carbon–carbon and carbon–heteroatom bond-forming transformations. The cycloaddition of two unsaturated fragments to generate a five-membered ring metallacycle is a key step in a number of important classes of multicomponent reactions, such as alkyne trimerization and Pauson–Khand reactions to form carbocycles. Dipolar cycloaddition reactions represent a useful general approach to assemble five-membered ring heterocycles. Multicomponent variants of these reactions often employ transition metal catalysis to mediate the efficient assembly of the 1,3-dipole.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.208
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.1060.000

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 head0.021
GPT teacher head0.275
Teacher spread0.253 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations12
Published2014
Admission routes1
Has abstractyes

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