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Functionalization and Homologation of C-H Bonds

2013· book-chapter· en· W3104867596 on OpenAlexaboutno aff
Douglass F. Taber

Bibliographic record

VenueOxford University Press eBooks · 2013
Typebook-chapter
Languageen
FieldChemistry
TopicOxidative Organic Chemistry Reactions
Canadian institutionsnot available
Fundersnot available
KeywordsAminationChemistrySurface modificationCatalysisOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Justin Du Bois of Stanford University developed (J. Am. Chem. Soc. 2010, 132, 10202) a Ru catalyst for the stereoretentive hydroxylation of 1 to 2. John T. Groves of Princeton University effected (J. Am. Chem. Soc. 2010, 132, 12847) equatorial chlorination of the test substrate 3. Kenneth M. Nicholas of the University of Oklahoma found (J. Org. Chem. 2010, 75, 7644) that I2 catalyzed the amination of 5. Thorsten Bach of the Technische Universität München established (Org. Lett. 2010, 12, 3690) that the amination of 7 proceeded with significant diastereoselectivity. Phil S. Baran of Scripps/La Jolla compiled (Synlett 2010, 1733) an overview of the development of C-H oxidation. Tethering can improve the selectivity of C-H functionalization. X. Peter Zhang of the University of South Florida devised (Angew. Chem. Int. Ed. 2010, 49, 10192) a Co catalyst for the cyclization of 9 to 10. Teck-Peng Loh of Nanyang Technological University established (Angew. Chem. Int. Ed. 2010, 49, 8417) conditions for the oxidation of 11 to 12. Jin-Quan Yu, also of Scripps/La Jolla, effected (J. Am. Chem. Soc. 2010, 132, 17378) carbonylation of methyl C-H of 13 to give 14. Sunggak Kim, now also at Nanyang Technological University, established (Synlett 2010, 1647) conditions for the free-radical homologation of 15 to 17. Gong Chen of Pennsylvania State University extended (Org. Lett. 2010, 12, 3414) his work on remote Pd-mediated activation by cyclizing 18 to 19. Many schemes have been developed in recent years for the oxidation of substrates to reactive electrophiles. Gonghua Song of the East China University of Science and Technology and Chao-Jun Li of McGill University reported (Synlett 2010, 2002) Fe nanoparticles for the oxidative coupling of 20 with 21. Zhi-Zhen Huang of Nanjing University found (Org. Lett. 2010, 12, 5214) that protonated pyrrolidine 25 was important for mediating the site-selective coupling of 24 with 23. Y. Venkateswarlu of the Indian Institute of Chemical Technology, Hyderabad, was even able (Tetrahedron Lett. 2010, 51, 4898) to effect coupling with a cyclic alkene 28. AB3217-A 32, isolated in 1992, was shown to have marked activity against two spotted spider mites. Christopher R. A. Godfrey of Syngenta Crop Protection, Münchwilen, prepared (Synlett 2010, 2721) 32 from commercial anisomycin 30a. The key step in the synthesis was the oxidative cyclization of 30b to 31.

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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.017
GPT teacher head0.186
Teacher spread0.169 · 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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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