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Record W4415693293 · doi:10.1021/acscatal.5c03642

Interrupted Carbonyl–Olefin Metathesis of Cyclic, Aliphatic Ketones

2025· article· en· W4415693293 on OpenAlexaff
Emily F. Traficante, Sean M. Burns, Junhyeong Kim, Daniel J. Nasrallah, Ho Ryu, Dongju Kim, Matthew S. Galliher, Haley Albright, Hannah L. Vonesh, Mu‐Hyun Baik, Corinna S. Schindler

Bibliographic record

VenueACS Catalysis · 2025
Typearticle
Languageen
FieldChemistry
TopicSynthetic Organic Chemistry Methods
Canadian institutionsUniversity of British Columbia
FundersNational Science Foundation Graduate Research Fellowship ProgramNational Institute of General Medical SciencesInstitute for Basic ScienceCamille and Henry Dreyfus FoundationAlfred P. Sloan FoundationDavid and Lucile Packard Foundation
KeywordsOlefin metathesisMetathesisOlefin fiberCatalysisReactivity (psychology)Salt metathesis reaction

Abstract

fetched live from OpenAlex

Functionalized pentalenes, indenes, naphthalenes and azulenes represent common structural motifs in many compounds of biological importance. We herein describe an iron-catalyzed synthetic strategy that enables access to these central scaffolds in two steps from commercial material. This method complements established transformations between carbonyl and olefin moieties, such as carbonyl–ene, Prins and carbonyl–olefin metathesis (COM) reactions as a fourth reactivity mode. Experimental and theoretical investigations support a mechanism that interrupts the carbonyl–olefin metathesis reaction pathway through the distinct fragmentation of intermediate oxetanes resulting in the direct formation of functionalized pentalenes, indenes, naphthalenes, and azulenes. The scope of this iron-catalyzed transformation between carbonyl and olefin functionalities is demonstrated with 19 examples proceeding in up to 99% yield.

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 score0.002
Threshold uncertainty score0.005

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 head0.010
GPT teacher head0.281
Teacher spread0.271 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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