Selecting Magnetic Resonance Imaging (MRI) Outcome Measures for Juvenile Idiopathic Arthritis (JIA) Clinical Trials: First Report of the MRI in JIA Special Interest Group
Bibliographic record
Abstract
Recent advances in magnetic resonance imaging (MRI) techniques have substantially improved the evaluation of joint pathologies in juvenile idiopathic arthritis (JIA). Because of the current availability of highly effective antirheumatic therapies and the unique and useful features of MRI, there is a growing need for an accurate and reproducible MRI assessment scoring system for JIA, such as the rheumatoid arthritis MRI Scoring (RAMRIS) for patients with rheumatoid arthritis (RA). To effectively evaluate the efficacy of treatment in clinical research trials, we need to develop and validate scoring methods to accurately measure joint outcomes, standardize imaging protocols for data acquisition and interpretation, and create imaging atlases to differentiate physiologic and pathologic joint findings in childhood and adolescence. Such a standardized, validated, JIA-MRI scoring method could be used as an outcome measure in clinical trials.
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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 | 0.175 | 0.217 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".