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Record W2520572099 · doi:10.1021/acs.organomet.6b00650

A Comparative Reactivity Survey of Some Prominent Bisphosphine Nickel(II) Precatalysts in C–N Cross-Coupling

2016· article· en· W2520572099 on OpenAlexafffund
Jillian S. K. Clark, Christopher M. Lavoie, Preston M. MacQueen, Michael J. Ferguson, Mark Stradiotto

Bibliographic record

VenueOrganometallics · 2016
Typearticle
Languageen
FieldChemistry
TopicCatalytic Cross-Coupling Reactions
Canadian institutionsUniversity of AlbertaDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaDalhousie University
KeywordsChemistryMorpholineReactivity (psychology)NickelArylCatalysisHalideCoupling reactionSubstrate (aquarium)Polymer chemistryMedicinal chemistryCombinatorial chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The synthesis and characterization of the new air-stable precatalyst ( L1 )Ni( o -tol)Cl ( C1; where L1 = JosiPhos CyPF-Cy) is reported, along with the results of a comparative reactivity survey involving C1 and analogous PAd-DalPhos- and DPPF-containing precatalysts ( C2 and C3, respectively) in representative nickel-catalyzed C(sp 2 )–N cross-coupling reactions. Precatalyst C1 was found to be competitive with, and in some cases complementary to, C2 in the monoarylation of ammonia and primary alkylamines with (hetero)aryl chlorides, including in otherwise challenging room temperature transformations. (Pseudo)halide comparison studies involving the cross-coupling of furfurylamine at room temperature revealed that in contrast to C2 precatalyst C1 performs less effectively with aryl bromides. Whereas C3 was found to be ineffective for such transformations, this DPPF-derived precatalyst proved superior to C1 and C2 in reactions involving the secondary dialkylamine test substrate morpholine.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.041
GPT teacher head0.316
Teacher spread0.274 · 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

Citations44
Published2016
Admission routes2
Has abstractyes

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