Peripheral Nerve Stimulation by Gradient Switching Fields in Magnetic Resonance Imaging
Bibliographic record
Abstract
A heterogeneous model of the human body and the scalar potential finite difference method are used to compute electric fields induced in tissue by magnetic field exposures. Two types of coils are considered that simulate exposure to gradient switching fields during magnetic resonance imaging (MRI). These coils producing coronal (y axis) and axial (z axis) magnetic fields have previously been used in experiments with humans. The computed fields can, therefore, be directly compared to human response data. The computed electric fields in subcutaneous fat and skin corresponding to peripheral nerve stimulation (PNS) thresholds in humans in simulated MRI experiments range from 3.8 to 5.8 V/m for the fields exceeded in 0.5% of tissue volume (skin and fat of the torso). The threshold depends on coil type and position along the body, and on the anatomy and resolution of the human body model. The computed values are in agreement with previously established thresholds for neural stimulation.
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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 | 0.000 |
| 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".