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Record W2313021027 · doi:10.3390/molecules21040448

Synthesis of Dense and Chiral Dendritic Polyols Using Glyconanosynthon Scaffolds

2016· article· en· W2313021027 on OpenAlexafffund
Tze Chieh Shiao, Rabindra Rej, Mariécka Rose, Giovanni M. Pavan, René Roy

Bibliographic record

VenueMolecules · 2016
Typearticle
Languageen
FieldMaterials Science
TopicDendrimers and Hyperbranched Polymers
Canadian institutionsUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDendrimerMonomerClick chemistryChirality (physics)MoietyValencyChemistryMaterials scienceCombinatorial chemistryPolymer chemistryOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

Most classical dendrimers are frequently built-up from identical repeating units of low valency (usually AB2 monomers). This strategy necessitates several generations to achieve a large number of surface functionalities. In addition, these typical monomers are achiral. We propose herein the use of sugar derivatives consisting of several and varied functionalities with their own individual intrinsic chirality as both scaffolds/core as well as repeating units. This approach allows the construction of chiral, dense dendrimers with a large number of surface groups at low dendrimer generations. Perpropargylated β-D-glucopyranoside, serving as an A5 core, together with various derivatives, such as 2-azidoethyl tetra-O-allyl-β-D-glucopyranoside, serving as an AB4 repeating moiety, were utilized to construct chiral dendrimers using "click chemistry" (CuAAC reaction). These were further modified by thiol-ene and thiol-yne click reactions with alcohols to provide dendritic polyols. Molecular dynamic simulation supported the assumption that the resulting polyols have a dense structure.

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 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 score0.007
Threshold uncertainty score0.349

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.013
GPT teacher head0.236
Teacher spread0.223 · 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

Citations11
Published2016
Admission routes2
Has abstractyes

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