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Record W2127794788 · doi:10.1002/cjce.20634

Simulation and experimental analysis of an intelligent tissue for controlled drug delivery

2011· article· en· W2127794788 on OpenAlexvenueno aff
Aboulfazl Barati, Saman Sotoudeh, Reza Davarnejad, Mohammad Aliabadi Farahani

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsnot available
Fundersnot available
KeywordsSelf-healing hydrogelsSwellingPolyethylene glycolDrug deliveryAcrylamidePEG ratioAcrylic acidMaterials scienceDiffusionBiomedical engineeringDrugChemistryChemical engineeringPolymer chemistryComposite materialPolymerNanotechnologyPharmacologyMonomerOrganic chemistryThermodynamicsPhysicsMedicineEngineering

Abstract

fetched live from OpenAlex

Abstract In this research, an antibiotic was loaded in the composites of polyethylene glycol (PEG), acrylamide (AAm) and acrylic acid (AAc) hydrogels matrices and their drug deliveries were tested. Effect of some parameters on the drug delivery was checked by UV‐spectrophotometer. Temperature enhancement considerably increased hydrogel swelling and the drug release in the AAc and AAm. A dynamic model based on the Maxwell–Stefan equation was developed to model the drug delivery of hydrogels. COMSOL software was also applied to simulate buffer diffusion inside the hydrogels.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.239
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations3
Published2011
Admission routes1
Has abstractyes

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