MétaCan
Menu
Back to cohort
Record W3126137416 · doi:10.1002/cctc.202001862

Cover Feature: Mechanistic Insights into Fe Catalyzed α‐C−H Oxidations of Tertiary Amines (ChemCatChem 1/2021)

2020· article· en· W3126137416 on OpenAlexaff
Christopher J. Legacy, Taylor O. Hope, Yohann Gagné, Frederick T. Greenaway, Mathieu Frenette, Marion H. Emmert

Bibliographic record

VenueChemCatChem · 2020
Typearticle
Languageen
FieldChemistry
TopicAsymmetric Hydrogenation and Catalysis
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsChemistryCatalysisAmideOxidizing agentKinetic isotope effectIntramolecular forceLigand (biochemistry)Reaction mechanismPhotochemistryOrganic chemistryDeuterium

Abstract

fetched live from OpenAlex

The Cover Feature shows cast iron catalysis: Trialkyl amines cooked with the right recipe will take the oxygen from water to form the corresponding trialkyl amide. This transformation is iron-catalyzed with a peroxyester acting as the oxidizing agent, picolinate as a ligand and pyridine as the solvent. In their Full Paper, C. J. Legacy et al. present mechanistic studies including initial rate kinetics, Eyring studies, kinetic isotope effects, a Hammett plot, reaction kinetic profile, oxidant probe study, EPR characterization of the iron site and DFT studies. Taken together, the data suggests a rate limiting step where an intramolecular α-C−H abstraction occurs on the amine bound to an Fe(IV)-oxo species. Tasty! More information can be found in the Full Paper by C. J. Legacy et al.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.137
Threshold uncertainty score0.458

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1370.039

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 head0.011
GPT teacher head0.223
Teacher spread0.212 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueChemCatChemSame topicAsymmetric Hydrogenation and CatalysisFrench-language works237,207