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Record W2520544386 · doi:10.1002/cmr.b.21327

A quadrature volume RF coil for vertical B<sub>0</sub> field open MRI systems

2016· article· en· W2520544386 on OpenAlexaff
Bogusław Tomanek, Vyacheslav Volotovskyy, Randy L. Tyson, Donghui Yin, Jonathan C. Sharp, Barbara Błasiak

Bibliographic record

VenueConcepts in Magnetic Resonance Part B · 2016
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsQuadrature (astronomy)Electromagnetic coilNuclear magnetic resonanceVolume (thermodynamics)Radiofrequency coilPhysicsMedicineNuclear medicineOptics

Abstract

fetched live from OpenAlex

Abstract Cylindrical quadrature radio frequency (RF) coils are widely used in magnetic resonance imaging and spectroscopy due to their high sensitivity and field uniformity. However, the field geometry is unsuitable for use in low‐field open magnetic resonance imaging (MRI) systems with vertical B0 field configurations. Therefore, a new design is proposed. A quadrature RF coil that combines Alderman‐Grant and Helmholtz designs was constructed to produce two independent modes, both orthogonal to the main magnetic field. The coil provides good RF homogeneity over a 20 × 15 × 15 cm volume and operates as both a transmit and receive coil. The application of the coil for 0.2 Tesla permanent magnet with a vertical B0 field is shown. The proposed coil may be applied to MR imaging of larger objects at low vertical magnetic fields.

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: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.005

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 science0.0010.000
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 head0.021
GPT teacher head0.335
Teacher spread0.314 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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