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Record W1999649954 · doi:10.1002/pola.26707

Designing responsive microgels for drug delivery applications

2013· article· en· W1999649954 on OpenAlex

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.

Bibliographic record

VenueJournal of Polymer Science Part A Polymer Chemistry · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDrug deliveryContext (archaeology)NanotechnologyBridge (graph theory)Materials scienceBiochemical engineeringDesign elements and principlesPolymer scienceComputer scienceEngineeringSoftware engineeringMedicineSurgery

Abstract

fetched live from OpenAlex

ABSTRACT Microgels based on thermally responsive polymers have been widely investigated in the context of controlled release applications, with increasing recent interest on developing a clearer understanding of what physical, chemical, and biological parameters must be considered to rationally design a microgel to deliver a specific drug at a specific rate in a specific physiological context. In this contribution, we outline these key design parameters associated with engineering responsive microgels for drug delivery and discuss several recent examples of how these principles have been applied to the synthesis of microgels or microgel‐based composites. Overall, we suggest that in vivo assessment of these materials is essential to bridge the existing gap between the fascinating properties observed in the lab and the practical use of microgels in the clinic. © 2013 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2013, 51, 3027–3043

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 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 score0.020
Threshold uncertainty score0.866

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.014
GPT teacher head0.251
Teacher spread0.237 · 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