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Record W2122134532 · doi:10.1109/iembs.2005.1615558

Potential Applications of Untethered Microdevices in the Blood Vessels within the Constraints of an MRI System

2005· article· en· W2122134532 on OpenAlexafffund
Jean‐Baptiste Mathieu, Gilles Soulez, Sylvain Martel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsUniversité de MontréalPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceBiomagnetismBiomedical engineeringEngineeringPhysicsMagnetic field

Abstract

fetched live from OpenAlex

This paper presents potential medical applications that an untethered microdevice in the cardiovascular system could perform within an MRI system. Recent developments and continuing evolution in micro/nano fabrication and design techniques will enable the development of functional microdevices able to explore the cardiovascular system. The Magnetic Resonance Submarine (MR-Sub) project is a first step towards this goal. Magnetic force generated by the gradient coils of an MRI system provides a propulsion mechanism that simplifies miniaturization and bypasses energetic challenges. Untethered microdevices may play an important complementary role in the next generation of minimally invasive tools. A better efficiency and targetability of the treatments will be achieved when microsystems such as the MR-Sub will allow a more extensive access to smaller blood vessels.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.225
Teacher spread0.219 · 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
Published2005
Admission routes2
Has abstractyes

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