Bibliographic record
Abstract
High signal-to-noise ratio (SNR) and the ability to acquire high-resolution thin section images are major advantages of 3 Tesla (T) that benefit musculoskeletal (MSK) imaging. Use of 3 T for pediatric MSK imaging is still in its early phase, and actual clinical benefits are not yet clear. However, initial reports in adult and our experience suggest that 3 T is better in imaging cartilage and small joints. It provides good quality images even for small field of views, which is advantageous in children. It shows cartilage, ligaments, and nerves better. After optimization, overall examination time is shorter at 3 T, which has the potential to reduce the need for sedation and increase throughput. 3-T imaging has the potential to improve small lesion evaluation and tumor staging, and it can be used for whole-body screening for metastasis. We discuss the technical differences, artifacts, and safety issues of 3 T, followed by our initial clinical experience with illustrative examples in pediatric MSK imaging at 3 T.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".