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Record W2875789373 · doi:10.1002/9781119390350.ch16

Dendritic Polymer Micelles for Drug Delivery

2018· other· en· W2875789373 on OpenAlexaff
Mosa Alsehli, Mario Gauthier

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMaterials Science
TopicDendrimers and Hyperbranched Polymers
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsDendrimerPolymerMonomerAmphiphileMicelleMacromoleculeDrug deliveryMoleculeCondensation reactionCombinatorial chemistryPolymer chemistryFunctional polymersChemistryMaterials scienceCopolymerOrganic chemistryAqueous solutionCatalysis

Abstract

fetched live from OpenAlex

Dendritic polymers are macromolecules with a multilevel highly branched architecture. Three distinct families of dendritic molecules can be identified, depending on the synthetic strategy used in their preparation. Dendrimers result from a strictly controlled sequence of polyfunctional ABn monomer protection, condensation, and deprotection reactions in a generation-based scheme. Hyperbranched polymers are mainly derived from analogous condensation reactions of ABn monomers, but typically without protecting groups and in one-pot reactions. Dendrigraft (or arborescent) polymers are obtained in a generation-based scheme analogous to dendrimers, but through grafting reactions of polymer segments rather than from small molecule building blocks. All three families of dendritic molecules can be further derivatized into water-dispersible species with micellar properties, for example, through the introduction of polar groups or hydrophilic polymer segments on the surface of the hydrophobic branched substrates, to serve as drug delivery vehicles. Different strategies for the synthesis of dendritic polymers, and their derivatization into amphiphilic micellar species, are discussed.

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: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.005

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 head0.011
GPT teacher head0.240
Teacher spread0.229 · 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
GenreOther

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

Citations1
Published2018
Admission routes1
Has abstractyes

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