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Record W2164029838 · doi:10.1115/1.4028943

Development of an MRI-Compatible, Compact, Rotary-Linear Piezoworm Actuator

2014· article· en· W2164029838 on OpenAlexaff
Khaled El Bannan, Blaine A. Chronik, Shaun P. Salisbury

Bibliographic record

VenueJournal of Medical Devices · 2014
Typearticle
Languageen
FieldEngineering
TopicSoft Robotics and Applications
Canadian institutionsWestern University
Fundersnot available
KeywordsRotary actuatorActuatorLinear actuatorTorqueMicrometerDistortion (music)Linear motionPneumatic actuatorStiffnessComputer scienceAcousticsControl theory (sociology)Materials scienceMechanical engineeringLinear motorEngineeringPhysicsStructural engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

A piezoelectric actuator was developed to operate safely deep inside the magnetic resonance imaging (MRI) machine bore. It is based on novel design that produces linear and rotary motion simultaneously increasing the accuracy of medical needle insertion procedures. The actuation method is based on the piezoworm principle, minimizing the actuator size, maximizing output force, and permitting micrometer scale insertion accuracy. Beryllium copper with high stiffness and strength was used in constructing the actuator to minimize image distortion and to achieve the targeted performance. Performance tests were performed by controlling the frequency input and observing the effect on speed, force and torque. The device achieved a linear speed of 5.4 mm/s and a rotary speed of 10.5 rpm.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.000
Threshold uncertainty score0.002

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 communication0.0000.000
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 head0.017
GPT teacher head0.277
Teacher spread0.260 · 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 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

Citations17
Published2014
Admission routes1
Has abstractyes

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