Bibliographic record
Abstract
To characterize the vibration properties as well as the acoustic noise properties of the gradient coil, a finite element (FE) model was developed using the dimensional design specifications of an available gradient coil insert and the concentration of the copper windings in the coil. This FE model was then validated using experimentally collected vibration data (experimental modal testing of the gradient coil in a free-free state (no boundary constraints)). Based on the validated FE model, boundary conditions (supports) were added to the model to simulate the operating condition when the gradient coil insert is in place in an MRI machine. Vibration analysis results from the FE model were again validated through experimental vibration testing, this time with the gradient coil insert installed in the MRI scanner and excited using swept sinusoidal time waveforms. The simulation results from the computational acoustic noise model were also validated through experimental noise measurement from the gradient coil insert in the MRI scanner using swept sinusoidal time waveform inputs. Comparisons show that the FE model predicts the vibration properties and the computational acoustic noise model predicts the noise characteristic properties extremely accurately.
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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".