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Record W1965233656 · doi:10.1115/1.3212556

Formation of Uniform Microspheres Using a Perforated Silicon Membrane: A Preliminary Study

2009· article· en· W1965233656 on OpenAlexaff
Ki‐Young Song, Mu Chiao, Boris Stoeber, Urs O. Häfeli, Madan M. Gupta, Wenjun Zhang

Bibliographic record

VenueJournal of Medical Devices · 2009
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvanced Drug Delivery Systems
Canadian institutionsUniversity of British ColumbiaUniversity of Saskatchewan
Fundersnot available
KeywordsMembrane emulsificationPLGAMicrosphereMaterials scienceMembranePhase (matter)SiliconDrug deliveryChemical engineeringCeramicNanotechnologyComposite materialNanoparticleChemistryOptoelectronicsOrganic chemistry

Abstract

fetched live from OpenAlex

This paper presents a new method to generate uniform microspheres with biodegradable poly(lactic-co-glycolic acid) (PLGA) material using microelectromechanical system technology. The general idea with this method is such that a liquid phase containing the dissolved microsphere matrix material reaches a continuous phase after a silicon membrane with micron-sized perforations, where microdroplets are formed. After the droplet is detached from the membrane, the solvent diffuses out of the droplets into a continuous phase leading to the formation of solid microspheres. The experiment was performed to verify this method with some promising result. It has been shown that with this method, about 90% of the microspheres are in the range from 1 to 2 μm, which seems to be better than the result obtained with other methods using glass or ceramic membranes. The microsphere with such a size range is useful for intravascular applications and pharmaceutical drug delivery with a slow release of the drug at narrowly defined rates.

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 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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.104
GPT teacher head0.451
Teacher spread0.348 · 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 teacher head, not a consensus.

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

Citations4
Published2009
Admission routes1
Has abstractyes

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