Peripheral nerve stimulation measures in a composite gradient system
Bibliographic record
Abstract
ABSTRACT Purpose: This work compared peripheral nerve stimulation (PNS) thresholds for the MRI scanner body gradients (BODY), a head/neck insert gradient (INSERT), and the combination of both gradient sets used simultaneously (COMPOSITE). Methods : For BODY, INSERT and COMPOSITE gradients, PNS thresholds were determined by exposing subject volunteers to stepped increases in gradient strength. For COMPOSITE mode, the INSERT was applied at equal (experiment 1) or double (experiment 2) the BODY gradient strength. Results: The locations and thresholds of peripheral nerve stimulation depended on the gradient system configuration, gradient axis, and gradient strength. Stimulation in the body occurred when using the BODY Y ‐gradient axis either singly (110 T/m/s) or in COMPOSITE mode (315 T/m/s experiment 2) and adding the insert gradient had negligible effect on stimulation. Stimulation in the head/sinus area generally occurred when using the INSERT X ‐gradient either singly (213 T/m/s) or in COMPOSITE mode (320 T/m/s) and adding the body gradient had negligible effect on stimulation. In the COMPOSITE mode, both the location of stimulation and the limiting gradient strength matched location and strength of the limiting component gradient. Conclusion: Stimulation, to a first‐order approximation, is independent for the two gradient systems. In COMPOSITE mode, PNS can be dominated by either of the individual gradient components, indicating that the contribution of each component can be increased until the threshold limit of each component gradient is reached. COMPOSITE gradients provide increased gradient performance with PNS thresholds higher than either component gradient system operating alone. © 2015 Wiley Periodicals, Inc. Concepts Magn Reson Part B (Magn Reson Engineering) 44B: 66–74, 2015
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".