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Record W1991285725 · doi:10.1063/1.3280171

Permanent magnet desktop magnetic resonance imaging system with microfabricated multiturn gradient coils for microflow imaging in capillary tubes

2010· article· en· W1991285725 on OpenAlexafffund
Ramin S. Sahebjavaher, Konrad Walus, Boris Stoeber

Bibliographic record

VenueReview of Scientific Instruments · 2010
Typearticle
Languageen
FieldEngineering
TopicMicrofluidic and Capillary Electrophoresis Applications
Canadian institutionsUniversity of British Columbia
FundersBritish Columbia Knowledge Development FundNatural Sciences and Engineering Research Council of CanadaUniversity of British Columbia
KeywordsMagnetMagnetic resonance imagingMaterials scienceNuclear magnetic resonanceCapillary actionPhysicsMedicineRadiology

Abstract

fetched live from OpenAlex

A prototype for a desktop high-resolution magnetic resonance imaging (MRI) velocimetry instrument to characterize flow fields in a capillary tube is demonstrated. This inexpensive compact system is achieved with a 0.6 T permanent magnetic configuration (Larmor frequency of 25 MHz) and temperature compensation using off-the-shelf NdFeB permanent magnets. A triaxial gradient module with microfabricated copper coils using a lithographic fabrication process has been developed. This gradient module is capable of generating fast-switching gradients (<100 micros) with amplitudes up to 1.7 T/m using custom made current amplifiers, and was optimized for microflow imaging. The radio frequency probe is integrated with the gradient module and is driven by custom electronics. A two-dimensional (2D) cross-sectional static image of the inside of a capillary tube with an inner diameter of 1.67 mm is acquired at an in-plane spatial resolution of better than 40 microm. Time-of-flight flow measurements were also obtained using this MRI system to measure the velocity profile of water flowing at average velocities of above 50 mm/s. The flow profile for slower flow velocities was obtained using phase-encoded techniques, which provides quantitative velocity information in 2D.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.409
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.005
GPT teacher head0.204
Teacher spread0.199 · 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

Citations17
Published2010
Admission routes2
Has abstractyes

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