MétaCan
Menu
Back to cohort
Record W2161014692 · doi:10.3390/molecules200916987

Designing Dendrimer and Miktoarm Polymer Based Multi-Tasking Nanocarriers for Efficient Medical Therapy

2015· review· en· W2161014692 on OpenAlex
Anjali Sharma, Ashok Kakkar

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

VenueMolecules · 2015
Typereview
Languageen
FieldMaterials Science
TopicDendrimers and Hyperbranched Polymers
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsNanocarriersDendrimerPolymerNanotechnologyComputer scienceMaterials scienceChemistryDrug deliveryPolymer chemistryOrganic chemistry

Abstract

fetched live from OpenAlex

To address current complex health problems, there has been an increasing demand for smart nanocarriers that could perform multiple complimentary biological tasks with high efficacy. This has provoked the design of tailor made nanocarriers, and the scientific community has made tremendous effort in meeting daunting challenges associated with synthetically articulating multiple functions into a single scaffold. Branched and hyper-branched macromolecular architectures have offered opportunities in enabling carriers with capabilities including location, delivery, imaging etc. Development of simple and versatile synthetic methodologies for these nanomaterials has been the key in diversifying macromolecule based medical therapy and treatment. This review highlights the advancement from conventional "only one function" to multifunctional nanomedicine. It is achieved by synthetic elaboration of multivalent platforms in miktoarm polymers and dendrimers by physical encapsulation, covalent linking and combinations thereof.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.072
GPT teacher head0.347
Teacher spread0.275 · 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