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Record W1525956711 · doi:10.1002/zaac.201400201

Tethered Bis(amidate) and Bis(ureate) Supported Zirconium Precatalysts for the Intramolecular Hydroamination of Aminoalkenes

2014· article· en· W1525956711 on OpenAlexafffund
Jean Michel P. Lauzon, Laurel L. Schafer

Bibliographic record

VenueZeitschrift für anorganische und allgemeine Chemie · 2014
Typearticle
Languageen
FieldChemistry
TopicAsymmetric Hydrogenation and Catalysis
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British Columbia
KeywordsHydroaminationProtonolysisZirconiumChemistryIntramolecular forceAmidePyridineLigand (biochemistry)Polymer chemistryThio-ChalcogenMedicinal chemistryStereochemistryCatalysisOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Tethered bis(amide) and bis(urea) proligands featuring a neutral chalcogen donor (O or S) in the backbone were synthesized and installed on zirconium via protonolysis. The bis(amidate) zirconium complexes adopt a κ4(N,N,O,O) binding motif and were characterized in the solid state with a pyridine donor. Likewise, the bis(ureate)‐supported complexes are also found to have a κ4(N,N,O,O) binding motif in the solid state however no additional donor ligand is required for discrete complex formation. No evidence for interaction between the neutral chalcogen donor and the zirconium atom is found for any of the transition metal species. All complexes were screened as precatalysts for the intramolecular hydroamination reaction with both primary and secondary aminoalkene substrates. Interestingly, the bis(ureate) species show similar reactivity to the bis(amidate) species, in contrast to a recently reported alkyl‐bridged bis(ureate) complex, which readily cyclizes secondary aminoalkenes.

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 score0.002

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 head0.007
GPT teacher head0.250
Teacher spread0.243 · 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

Citations17
Published2014
Admission routes2
Has abstractyes

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