Preliminary Definitions for Sacroiliac Joint Pathologies in the OMERACT Juvenile Idiopathic Arthritis MRI Score (OMERACT JAMRIS‐SIJ)
Bibliographic record
Abstract
Purpose Clinical assessment of the Sacroiliac Joint (SIJ) has limitations due to the location and anatomy of the joint. Magnetic Resonance Imaging is a sensitive, non‐invasive tool in detecting early SIJ inflammatory changes and structural damage in Juvenile Idiopathic Arthritis (JIA). The quantification of interval change of pediatric SIJs using an MRI based scoring methods will serve as an important objective outcome measure for the assessment disease severity and treatment effectiveness in JIA. Methods The OMERACT consensus‐driven methodology consisting of iterative surveys and focus group meetings within an international group of pediatric rheumatologists and radiologist was utilized to decide the measurement construct, items, and definitions. Consensus was deemed to have been achieved if greater than 70% agreement was reached among voting attendees at the session in the absence of greater than 15% present or more in strong disagreement. Results Twenty‐eight international multidisciplinary experts from North America, Europe, South Asia, and South America participated in the study. Two domains, inflammation and structural, were identified. Definitions for bone marrow edema, joint space inflammation, capsulitis, and enthesitis were derived for joint inflammation; sclerosis, erosion, fatty lesion and ankylosis were defined for assessing structural joint changes. Conclusion Preliminary consensus‐driven definitions for inflammation and structural elements have been derived, underpinning the ongoing development of the Juvenile arthritis SIJ MRI scoring system (JAMRIS‐SIJ). Support or Funding Information Hospital for SickKids Research Trainee Fund (RESTRACOMP) This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0.018 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 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".