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Record W2797243333

Design of a MRI Compatible Faraday Cage for Syringe Pumps

2017· article· en· W2797243333 on OpenAlexaff
Richard Dyrkacz, Lawrence Ryner, Chad Harris, Daniel W. Rickey, Ron Cappellani, Prakashen Govender

Bibliographic record

VenueCMBES Proceedings · 2017
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsHealth Sciences CentreCancerCare ManitobaWinnipeg Regional Health Authority
Fundersnot available
KeywordsSyringeFaraday cageSyringe driverCageMaterials scienceMagnetic fieldPhysicsMechanical engineeringEngineering
DOInot available

Abstract

fetched live from OpenAlex

The goal of this project was to design a MRI compatible Faraday cage for syringe pumps that do not display any artefacts during a MRI scanning procedure. A Faraday cage was fabricated consisting of stainless steel that contained a Medfusion ® 3500 syringe pump and a power supply unit. When the syringe pump was running with water flowing at a rate of 3 mL/hour in a 1.6 Gauss magnetic field, artefacts appeared during the MRI scans. Once the syringe pump was placed inside the Faraday cage and ran on its own battery power, no artefacts appeared on any of the MRI scans. The syringe pump was then connected to a power outlet using an extension cord; slight artefacts appeared on the MRI scans. Although the Faraday cage can prevent artefacts from appearing on MRI scans, it is strongly recommended that they run on their own battery power.

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 score0.686
Threshold uncertainty score0.354

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 head0.073
GPT teacher head0.367
Teacher spread0.294 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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