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Record W4311716211 · doi:10.26434/chemrxiv-2022-dpsx9

Mechanochemical Desymmetrization of Unbiased Bis- and Tris-alkynes to Access 3,5-Isoxazoles-Alkyne Adducts and Unsymmetrical Bis-3,5-isoxazoles

2022· preprint· en· W4311716211 on OpenAlexafffund
Rafael A. Hernandez R., Irini Trakakis, Jean‐Louis Do, Louis A. Cuccia, Tomislav Friščić, Pat Forgione

Bibliographic record

VenueChemRxiv · 2022
Typepreprint
Languageen
FieldChemistry
TopicAsymmetric Synthesis and Catalysis
Canadian institutionsMcGill UniversityConcordia University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaCentre in Green Chemistry and Catalysis
KeywordsAlkyneIsoxazoleAdductTrisChemistryNitrileCycloadditionYield (engineering)DesymmetrizationCombinatorial chemistryMedicinal chemistryOrganic chemistryCatalysisMaterials science

Abstract

fetched live from OpenAlex

A mechanochemical desymmetrization of symmetrical bis- and tris-alkynes via a controlled 1,3-dipolar cycloaddition reaction with nitrile oxide dipoles has been developed. This convenient, efficient, and simple protocol allows access to 3,5-isoxazole-alkyne adducts from easily prepared or commercially available symmetrical bis- and tris-alkynes in moderate to excellent yield. The synthetic utility of 3,5-isoxazole-alkyne was demonstrated by developing a route to access β-ketoenamine-alkyne derivatives and the synthesis of unsymmetrical bis-3,5-isoxazoles products in good to excellent yields.

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 score0.005

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)0.0010.001

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 head0.032
GPT teacher head0.286
Teacher spread0.253 · 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

Citations0
Published2022
Admission routes2
Has abstractyes

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