Optimizing the gVERSE RF Pulse Sequence: An Evaluation of Two Competitive Software Algorithms
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Radio Frequency (RF) pulses cause elevated patient temperatures during Magnetic Resonance Imaging (MRI) procedures. Generalized Variable Rate Selective Excitation (gVERSE) is a co-design method for Radio Frequency (RF) pulse and slice gradient which minimizes Specific Absorption Rate (SAR) (the accepted predictor of patient heating). After developing a rigorous mathematical model, the nonlinear gVERSE optimization problem is solved using two competitive software packages. The gVERSE solutions generated by Sparse Optimal Control Software (SOCS) and AMPL-MINOS produce two separate variations of SAR reducing pulses. The different software solutions are compared using numerical simulations of slice selection. The computational experiments involved with the gVERSE model provided insight towards using different software to solve highly demanding mathematical optimization problems.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it