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Record W2320745871 · doi:10.1021/ol500075h

Organoselenium-Catalyzed Mild Dehydration of Aldoximes: An Unexpected Practical Method for Organonitrile Synthesis

2014· article· en· W2320745871 on OpenAlexaff
Lei Yu, Hongyan Li, Xu Zhang, Jianqing Ye, Jianping Liu, Qing Xu, Mark Lautens

Bibliographic record

VenueOrganic Letters · 2014
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicOrganoselenium and organotellurium chemistry
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsChemistryDehydrationCatalysisCombinatorial chemistryOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

Areneselenenic acids (ArSeOH), readily generated from diaryl diselenides and H2O2 by in situ oxidation, were found to be effective and reusable catalysts for dehydration of aldoximes, leading to a practical and scalable preparation of useful organonitriles under mild conditions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.031
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.060
GPT teacher head0.401
Teacher spread0.341 · 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 teacher head, not a consensus.

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

Citations154
Published2014
Admission routes1
Has abstractyes

Explore more

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