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Record W3209096041 · doi:10.33774/chemrxiv-2021-jdmn0

Efficient Synthesis of Azido Sugars using Fluorosulfuryl Azide Diazotransfer Reagent

2021· preprint· en· W3209096041 on OpenAlexafffund
Chantelle J. Capicciotti, Joshua M. Kofsky, Gour Chand Daskhan, Matthew S. Macauley

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldChemistry
TopicClick Chemistry and Applications
Canadian institutionsUniversity of AlbertaQueen's University
FundersNatural Sciences and Engineering Research Council of CanadaBanting Research Foundation
KeywordsAzideChemistryReagentBioconjugationYield (engineering)GlycosylCombinatorial chemistrySugarAmine gas treatingOrganic chemistryProtecting group

Abstract

fetched live from OpenAlex

Azide-containing sugars are important tools for the synthesis of biologically relevant 1,2-cis-glycosides and for bioconjugation chemistry. Previous strategies for the installation of a non-participating C2-azido functionality use harsh conditions and long reaction times. Herein, we report the synthesis of azido sugars using fluorosulfuryl azide (FSO2N3; 1) with a Cu(II) catalyst as a safe and efficient diazotransfer reagent. Common hexosamine substrates were converted to 2-azido-2-deoxy sugars in less than 5 minutes in quantitative yield. Glycosyl donors with orthogonal protecting groups were readily prepared from these azido sugars with good overall yield and a single column purification. The diazotransfer protocol was also efficiently used on other amino sugar derivatives, including aminoglycosides and substrates with amine-containing linkers. This optimized method will expand access to important non-participating C2-azido protecting groups and other azido sugar derivatives.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.030
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.030
GPT teacher head0.274
Teacher spread0.244 · 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
Published2021
Admission routes2
Has abstractyes

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