Heating of metallic rods induced by time‐varying gradient fields in MRI
Bibliographic record
Abstract
PURPOSE: To develop and validate an analytical technique to estimate the heating of metallic rods by magnetic resonance imaging (MRI) gradient fields to aid developers of MRI-compatible devices. MATERIALS AND METHODS: Twelve rods (12.7 mm diameter, 127 mm long) were used. The magnetic field was provided by a custom-made water-cooled solenoid driven by a 1 kHz sinusoidal waveform with a 7.2 A peak current. The sample was insulated with polystyrene and the temperature measured using an MR-compatible thermocouple system (Sa1-E from Omega). Measurements were recorded using a National Instruments SCXI-1303. The AC/DC module of COMSOL 3.4 was used for finite element analysis of the power deposited. RESULTS: Finite element analysis (FEA) showed good correspondence with the analytical estimates for the rod parallel to the field and then FEA was used to determine the scaling function for the rod perpendicular to the field. The experimental results showed good correlation with the theoretical estimate when the finite length of the test coil was accounted for. CONCLUSION: A new scaling function for the rod perpendicular to the field was developed. Heating in this orientation is double that of the parallel case. The results will aid developers of MRI-compatible devices in estimating heating before testing in the MRI.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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".