MétaCan
Menu
Back to cohort
Record W2109825916 · doi:10.1002/ejoc.201402802

Controlled Acid‐Mediated Regioselective <i>O</i>‐Desilylations for Multifunctionalization of Cyclodextrins

2014· article· en· W2109825916 on OpenAlexafffund
Jiamin Gu, Tong Chen, Ping Zhang, Chang‐Chun Ling

Bibliographic record

VenueEuropean Journal of Organic Chemistry · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical Synthesis and Analysis
Canadian institutionsAlberta Glycomics CentreUniversity of Calgary
FundersAlberta Innovates - Technology FuturesGovernment of AlbertaUniversity of Calgary
KeywordsChemistryRegioselectivitySilylationSilyl etherTetraReactivity (psychology)CyclodextrinSurface modificationEtherCombinatorial chemistryOrganic chemistryMedicinal chemistryStereochemistryCatalysis

Abstract

fetched live from OpenAlex

Abstract A highly valuable tri‐/tetra‐functionalization method is reported for cyclodextrin (CD) chemistry by taking advantage of the acid‐sensitivity of the O ‐silyl ether group and also the geometry of CD macrocycles. The controlled acid‐mediated O ‐desilylations from the easily accessible per‐3,6‐ O ‐silylated CD derivatives provide unprecedented regioselectivity to differentiate not only primary O ‐silyl groups from secondary groups, but also O ‐silyl groups of the same type with identical chemical reactivity. This methodology differs from other conventional monofunctionalization methods of natural CDs, which only allow for a direct twofold differentiation of hydroxyl groups in a CD, because the current method permits the synthesis of tri‐ and tetra‐functionalized CDs in a short reaction sequence. Most importantly, the developed method has been found to be applicable to all α‐, β‐, and γ‐CDs and the obtained CD intermediates are versatile. Furthermore, we demonstrate that these processes are practical and can be carried out on multigram scales.

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 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 score0.135
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0000.000

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 head0.006
GPT teacher head0.201
Teacher spread0.196 · 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.

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

Citations7
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueEuropean Journal of Organic ChemistrySame topicChemical Synthesis and AnalysisFrench-language works237,207