In Vivo 7.0-Tesla Magnetic Resonance Imaging of the Wrist and Hand: Technical Aspects and Applications
Bibliographic record
Abstract
Magnetic resonance imaging (MRI) at 7.0 T has the potential for higher signal-to-noise ratio (SNR), improved spectral resolution, and faster imaging compared with 1.5-T and 3.0-T MR systems. This is especially interesting for challenging imaging regions like the wrist and the hand because of the small size of the visualized anatomical structures; the increase in SNR could then be directly converted into higher spatial resolution of the images. Practically, imaging at 7.0 T poses a variety of technical challenges such as static (B (0)) and radiofrequency (B (1)) homogeneities, shimming, chemical shift artifacts, susceptibility artifacts, alterations in tissue contrast, specific absorption rate limitations, coil construction, and pulse sequence tuning. Despite these limitations, this first experience in anatomical imaging of the wrist and the hand at 7.0 T is very promising. Functional imaging techniques will gain importance at ultra-high-field MRI and need to be assessed in detail in the future.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".