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Record W3120002196 · doi:10.1021/acscatal.0c04956

Synthesis of Carbocyclic Compounds via a Nickel-Catalyzed Carboiodination Reaction

2021· article· en· W3120002196 on OpenAlexafffund
Austin D. Marchese, Timur Adrianov, Martin F. Köllen, Bijan Mirabi, Mark Lautens

Bibliographic record

VenueACS Catalysis · 2021
Typearticle
Languageen
FieldChemistry
TopicCatalytic C–H Functionalization Methods
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of TorontoDeutscher Akademischer Austauschdienst
KeywordsSN2 reactionChemistryCatalysisSteric effectsNickelNucleophileReductive eliminationCombinatorial chemistryYield (engineering)HeteroatomLigand (biochemistry)Oxidative additionMalonateOrganic chemistryMedicinal chemistryRing (chemistry)Materials science

Abstract

fetched live from OpenAlex

A scalable nickel-catalyzed carboiodination reaction generating 6-membered carbocycles is reported. NiI 2 and P(OEt) 3, as the ligand and reducing agent, provided decorated iodo-tetrahydronaphthalenes in up to 94% yield. The impact of varying electronic and steric parameters on the reaction are reported and a non-linear Hammett plot was obtained, supporting a change in the rate-determining step from oxidative addition to reductive elimination. Experimental and DFT studies suggest that the malonate group may stabilize a nickel oxidative-addition complex. A variety of heteroatom-containing nucleophiles and medicinally relevant heterocycles were easily incorporated into the products via simple S N 2 chemistry.

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 integrity0.0000.001
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 head0.018
GPT teacher head0.269
Teacher spread0.251 · 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

Citations39
Published2021
Admission routes2
Has abstractyes

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Same venueACS CatalysisSame topicCatalytic C–H Functionalization MethodsFrench-language works237,207