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Record W2128242388 · doi:10.1109/ccece.2003.1226190

Design and implementation of MEMS based microneedles for biomedical applications

2004· article· en· W2128242388 on OpenAlexafffund
Priyanka Aggarwal, K.V.I.S. Kaler, Wael Badawy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvancements in Transdermal Drug Delivery
Canadian institutionsUniversity of Calgary
FundersUniversity of Calgary
KeywordsTransdermalMicroelectromechanical systemsMaterials scienceBiomedical engineeringDrug deliveryBlood samplingRapid prototypingNanotechnologyComposite materialEngineeringMedicine

Abstract

fetched live from OpenAlex

This paper addresses the practical design and implementation MEMS (microelectro-mechanical system) based in-plane silicon microneedles for transdermal drug delivery and/or blood sampling for biomedical and biotechnology applications. The characteristics of in-plane microneedles are far more reliable than out-of-plane microneedles for transdermal drug delivery and blood sampling. In order to obtain the sample of blood from the subcutaneous fat layer, which occurs at a distance of 2000 to 4000 /spl mu/m below the skin surface, the length of our MEMS based in-plane microneedle have been set at 3000 /spl mu/m. This microneedle length is impractical for out-of-plane microneedles. Drug delivery and blood samplings place requirement in terms of minimal needle dimensions and force withstanding capabilities, which are inversely related to each other. The strength of the microneedles has been examined analytically and modeled using finite element modeling tools. Through performance analysis it is shown that the proposed design is a significant improvement over existing microneedles.

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)0.000
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: Methods · Consensus signal: none
Teacher disagreement score0.862
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.101
GPT teacher head0.469
Teacher spread0.368 · 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
GenreMethods

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

Citations7
Published2004
Admission routes2
Has abstractyes

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