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Record W2766444972 · doi:10.1049/el.2017.3568

Magnetic field probes for time‐domain monitoring of RF exposure within tissue‐mimicking materials for MRI‐compatible medical device testing

2017· article· en· W2766444972 on OpenAlexaff
Ali Attaran, William B. Handler, Ravi S. Menon, Blaine A. Chronik

Bibliographic record

VenueElectronics Letters · 2017
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Measurements
Canadian institutionsWestern University
Fundersnot available
KeywordsBiomedical engineeringMaterials scienceRadio frequencyField (mathematics)Time domainNuclear magnetic resonanceElectronic engineeringComputer scienceEngineeringElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

A new RF B/H field probe for time‐domain monitoring of RF electromagnetic‐radiated exposure during medical device testing inside the lossy tissue‐mimicking material is presented. The probe was tuned and matched for a centre frequency of 127.6 MHz to optimise the response for testing within typical 3T MRI scanners or RF exposure platforms. A 5 mm radius loop was chosen as a trade‐off between spatial resolution and sensitivity and fabricated on a double‐sided FR4 PCB. In the presented scheme, a low‐noise RF amplifier was employed to reduce the sensitivity of the probe to induce voltage on the transmission lines and to improve accuracy. The implemented probe was found to provide acceptable spatial resolution and sensitivity for reliable B/H field mapping for this application.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 integrity0.0010.000
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 head0.021
GPT teacher head0.258
Teacher spread0.237 · 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
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

Citations12
Published2017
Admission routes1
Has abstractyes

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