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Record W4388731690 · doi:10.26434/chemrxiv-2023-ltgjf

Reversible 1,2-Methyl Migration to an N-Heterocyclic Carbene in a PCNHCP Cobalt(I) Complex Enables Stereoselective (E and Z) Allyl Ether Isomerization

2023· preprint· en· W4388731690 on OpenAlexfundno aff
Subhash Garhwal, Sakthi Raje, Katarzyna Młodzikowska‐Pieńko, Tofayel Sheikh Mohammed, Ron Raphaeli, Natalia Fridman, Linda J. W. Shimon, Renana Poranne, Graham de Ruiter

Bibliographic record

VenueChemRxiv · 2023
Typepreprint
Languageen
FieldChemistry
TopicCatalytic Cross-Coupling Reactions
Canadian institutionsnot available
FundersAzrieli FoundationIsrael Science Foundation
KeywordsIsomerizationCobaltCarbeneStereoselectivityChemistryPincer movementEtherCationic polymerizationSubstituentSteric effectsMigratory insertionCatalysisEnol etherMedicinal chemistryStereochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

With growing efforts pushing towards sustainable catalysis, using earth-abundant metals has become increasingly important. Here we present the first examples of cobalt PCNHCP pincer complexes that demonstrate dual stereoselectivity for allyl ether isomerization. While the cationic cobalt complex [((PCNHCP)Co)2-μ-N2][BAr4F]2 (3) affords the Z-isomer of the enol ether predominantly, the corresponding methyl complex [(PCNHCP)CoMe)] (4) mostly gives the E-isomer. The dichotomy in selectivity is investigated computationally, revealing important contributions from the steric profile of the substituents on the metal (Me or N2), including an unprecedented migration of the methyl substituent from cobalt to the N-heterocyclic carbene carbon, which is further explored in this report.

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 score0.003
Threshold uncertainty score0.009

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)0.0030.001

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 head0.057
GPT teacher head0.319
Teacher spread0.262 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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