Feasibility and Reliability of the Spondyloarthritis Research Consortium of Canada Sacroiliac Joint Structural Score in Children
Bibliographic record
Abstract
OBJECTIVE: There is a critical need for measures to evaluate structural progression in the pediatric sacroiliac joint (SIJ). We aimed to evaluate the construct validity and reliability of the Spondyloarthritis Research Consortium of Canada SIJ Structural Score (SSS) in children with suspected or confirmed juvenile spondyloarthritis. METHODS: The SSS assesses structural lesions of the SIJ on magnetic resonance imaging (MRI) through the cartilaginous part of the joint. We conducted 3 sequential reading exercises with 6 readers (1 adult and 3 pediatric radiologists, 1 adult and 1 pediatric rheumatologist). Each exercise was preceded by a calibration module. Interobserver reliability was assessed using intraclass correlation coefficients (ICC). Prespecified acceptable reliability thresholds were ICC > 0.5 for erosion, backfill, and sclerosis, and ICC > 0.7 for ankylosis and fat metaplasia. RESULTS: The SSS had face validity and was feasible to score in pediatric cases for all 3 reading exercises. Of the cases used in the 3 exercises, 58% were male and the median age was 14 years (range 6.8-18.7 yrs). After calibration, median ICC across all readers for each SSS component were the following: erosion 0.67 (interquartile range 0.54-0.80), backfill 0.33 (0.19-0.52), fat metaplasia 0.74 (0.62-0.85), sclerosis 0.63 (0.48-0.77), and ankylosis 0.44 (0.28-0.62). Prespecified reliability thresholds were achieved in the third exercise for erosion, sclerosis, and fat metaplasia but not for backfill or ankylosis. CONCLUSION: The SSS was feasible to score and had acceptable reliability for pediatric SIJ MRI evaluation. The ICC improved with additional calibration and reading exercises, even for readers with limited experience.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".