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Record W2513524591 · doi:10.1002/tcr.201600080

Iron Group Hydrides in Noyori Bifunctional Catalysis

2016· article· en· W2513524591 on OpenAlexafffund
Robert H. Morris

Bibliographic record

VenueThe Chemical Record · 2016
Typearticle
Languageen
FieldChemistry
TopicAsymmetric Hydrogenation and Catalysis
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaKillam TrustsUniversity of TorontoCanada Council for the Arts
KeywordsTransfer hydrogenationChemistryHydrideBifunctionalNoyori asymmetric hydrogenationRutheniumAmideDenticityCatalysisOsmiumEnantioselective synthesisAmine gas treatingOrganic chemistryCombinatorial chemistryHydrogenMetal

Abstract

fetched live from OpenAlex

This is an overview of the hydride-containing catalysts prepared in the Morris group for the efficient hydrogenation of simple ketones, imines, nitriles and esters and the asymmetric hydrogenation and transfer hydrogenation of prochiral ketones and imines. The work was inspired by and makes use of Noyori metal-ligand bifunctional concepts involving the hydride-ruthenium amine-hydrogen HRuNH design. It describes the synthesis and some catalytic properties of hydridochloro, dihydride and amide complexes of ruthenium and in one case, osmium, with monodentate, bidentate and tetradentate phosphorus and nitrogen donor ligands. The iron hydride that has been identified in a very effective asymmetric transfer hydrogenation process is also mentioned. The link between the HMNH structure and the sense of enantioinduction is demonstrated by use of simple transition state models.

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 score0.001
Threshold uncertainty score0.004

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)0.0010.000

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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

Citations37
Published2016
Admission routes2
Has abstractyes

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