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Record W4413838569 · doi:10.24908/iqurcp19853

Development and Optimization of Nickel-Catalyzed Suzuki-Miyaura Cross-Coupling Reaction of Tertiary Sulfones.

2025· article· en· W4413838569 on OpenAlexvenueno aff
E. C. Hsu, Alannah Constable

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2025
Typearticle
Languageen
FieldChemistry
TopicSulfur-Based Synthesis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsNickelCatalysisCoupling reactionChemistryCoupling (piping)Combinatorial chemistryMaterials scienceOrganic chemistryMetallurgy

Abstract

fetched live from OpenAlex

Suzuki-Miyaura cross-coupling reactions are a popular and useful synthetic method to create new carbon-carbon bonds, due to their relative safety and stability.1 In particular, this method has shown promise in the construction of densely functionalized quaternary carbon stereocenters that can be bulky and otherwise difficult to synthesize, making it optimal for synthesizing pharmaceuticals and natural products.1,2 Tertiary sulfones are a class of compounds that are highly versatile and have demonstrated abilities to serve as unique pseudohalides and electrophilic coupling partners, which allows for added flexibility in this powerful reaction.3 In previous work done by the Crudden group, a variety of benzylic and allylic tertiary sulfones were used to produce quaternary carbon centers, however it required naphthyl or similar p-extended groups in order to facilitate coordination of nickel-catalyzed Suzuki couplings.4 We are currently investigating the possibility of using tertiary sulfones containing conjugated olefins to overcome this limitation. This would further enhance the utility of this reaction, allowing access to synthetically challenging products with a conjugated olefin backbone that can be further functionalized, serving as a versatile lynchpin handle. This work will enable direct and efficient synthesises of natural products and further develop the scope of pharmaceutical compounds. [1] - Roughley, S. D.; Jordan, A. M. J. Med. Chem. 2011, 54, 3451-3479. [2] - Ling, T.; Garfias, J. M.; Lawson, S. L.; Rivas, F. Tetrahedron. 2025, 183, 134711. [3] - Trost, B. M.; Chem-Eur J. 2019, 25, 11193 – 1121. [4] - Ariki, Z. T.; Maekawa, Y.; Nambo, M.; Crudden, C. M. J. Am. Chem. Soc. 2017, 140 (1), 78–81.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.068
GPT teacher head0.366
Teacher spread0.298 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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