Permanent magnet desktop magnetic resonance imaging system with microfabricated multiturn gradient coils for microflow imaging in capillary tubes
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".