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A Non-Magnetic RF Balun Designed at 128 MHz Centre frequency for 3 T MRI Scanners

2020· article· en· W3110176998 on OpenAlexaff
Ali Dianat, Ali Attaran, Roberto Muscedere, Blaine A. Chronik

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsWestern UniversityUniversity of Windsor
Fundersnot available
KeywordsBalunMaterials scienceRadio frequencyPrinted circuit boardSIGNAL (programming language)CopperFootprintNuclear magnetic resonanceMagnetic resonance imagingAntenna (radio)OptoelectronicsElectrical engineeringPhysicsEngineeringComputer science

Abstract

fetched live from OpenAlex

In this work, a non-magnetic RF balun is implemented for 3 T magnetic resonance imaging (MRI) scanners operating at 128 MHz to transform a balanced input signal from a dipole or loop antenna into an unbalanced output signal. It is fabricated on a low-cost, copper cladded four-layer printed circuit board (PCB), FR4 with a thickness of 1.57 mm and a copper thickness of 35 μm, with overall footprint of 11.6 mm × 12.2 mm. A comparison among the ADS RF momentum simulations and the measured results indicates a good agreement with the measured insertion and return losses of better than -1 dB and -13 dB, respectively, in a 50 Ω termination setting.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score1.000

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)0.0020.001

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 head0.013
GPT teacher head0.198
Teacher spread0.185 · 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.

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

Citations3
Published2020
Admission routes1
Has abstractyes

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