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Record W2133308348 · doi:10.1039/c3cs60090d

How do multivalent glycodendrimers benefit from sulfur chemistry?

2013· review· en· W2133308348 on OpenAlex
Marc Gingras, Yoann M. Chabre, Myriam Roy, René Roy

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueChemical Society Reviews · 2013
Typereview
Languageen
FieldMaterials Science
TopicDendrimers and Hyperbranched Polymers
Canadian institutionsUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsAgence Nationale de la Recherche
KeywordsChemistryDendrimerNanotechnologyGlycobiologyCarbohydrate chemistrySulfurOrganic chemistryMaterials scienceBiochemistryGlycan

Abstract

fetched live from OpenAlex

Sulfur-containing glycodendrimers have steadily emerged over a few decades and this review describes the first survey of this field. Although the contribution of sulfur chemistry to glycodendrimers could be seen at the moment as a development of various linking strategies, there is more than synthesis because the presence of sulfur itself modulates unique photophysical and electrochemical properties. This fact has long been recognized in materials science, for instance. Emphasis on the numerous advantages of sulfur in glycosylated dendrimers is thus put forward in this review. The synergy between sulfur, dendrimers, and carbohydrate chemistry conveys novel synthetic avenues, properties, and applications toward innovative perspectives in chemistry, glycobiology, materials science and nanoscience, with a particular significance for biosensors.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.883
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.003

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 head0.054
GPT teacher head0.298
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