Evaluation of a positron emission tomography (PET)‐compatible field‐cycled MRI (FCMRI) scanner
Bibliographic record
Abstract
Field-cycled MRI (FCMRI) uses two independent, actively controlled resistive magnets to polarize a sample and to provide the magnetic field environment during data acquisition. This separation of tasks allows for novel forms of contrast, reduction of susceptibility artifacts, and a versatility in design that facilitates the integration of a second imaging modality. A 0.3T/4-MHz FCMRI scanner was constructed with a 9-cm-wide opening through the side for the inclusion of a photomultiplier-tube-based positron emission tomography (PET) system. The performance of the FCMRI scanner was evaluated prior to integrating PET detectors. Quantitative measurements of the system's signal, phase, and temperature were recorded. The polarizing and readout magnets could be operated continuously at 100 A without risk of damage to the system. Transient instabilities in the readout magnet, caused by the pulsing of the polarizing magnet, dissipated in 50 ms; this resulted in a steady-state homogeneity of 32 Hz over a 7-cm-diameter volume. The short- and long-term phase behaviors of the readout field were sufficiently stable to prevent visible readout or phase-encode artifacts during imaging. Preliminary MR images demonstrated the potential of the FCMRI scanner and the efficacy of integrating a PET system.
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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 | 0.002 | 0.004 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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 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".