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N, O-polydentate ligands for palladium-catalyzed cross-coupling reactions (Part III)

2021· article· en· W3210877954 on OpenAlexaff
Archana Rajmane, Sanjay Jadhav, Arjun Kumbhar

Bibliographic record

VenueJournal of Organometallic Chemistry · 2021
Typearticle
Languageen
FieldChemistry
TopicCatalytic Cross-Coupling Reactions
Canadian institutionsUniversity of Alberta
FundersUniversity Grants Commission
KeywordsChemistryPhosphineDenticityCatalysisPalladiumCarbeneHomogeneous catalysisCoupling reactionCombinatorial chemistryOrganic chemistryMetal

Abstract

fetched live from OpenAlex

The Pd catalyzed cross-coupling reactions have played a crucial role in accomplishing different valuable organic transformations. These transformations involve the use of homogeneous as well as heterogeneous Pd catalysts. A large variety of ligands have been used in Pd catalyzed coupling reactions. Traditionally, these transformations have been carried out by various phosphine-based ligands. The phosphine ligands are suffering from poor air, moisture, and thermal stability. Hence, in recent years phosphine-free ligands such as N-heterocyclic carbenes and amines have been attracted great attention in the field of catalysis. Though the N-containing ligands have showed comparatively low activity as compared to phosphine and carbene-based ligands, most importantly, these complexes have broad scope in catalysis, as they represent a low cost, less toxic, good moisture, thermal and air stability as well as environmentally friendly. In this review, we present the developments made in the field of Pd complexes of N and O donor ligands in various cross-coupling reactions.

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: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

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)0.0020.001

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 head0.021
GPT teacher head0.293
Teacher spread0.272 · 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

Citations19
Published2021
Admission routes1
Has abstractyes

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