Determination of Relative Weightings for Sacroiliac Joint Pathologies in the OMERACT Juvenile Arthritis Magnetic Resonance Imaging Sacroiliac Joint Score
Bibliographic record
Abstract
This study aims to determine the relative weights (point value) of items of the juvenile idiopathic arthritis magnetic resonance imaging-sacroiliac joint scoring system (JAMRIS-SIJ). An adaptive multicriteria decision analysis was performed using the 1000Minds web application to determine the relative weights of the items in the JAMRIS-SIJ inflammation and damage domains. Experts in imaging and rheumatology independently completed a conjoint analysis survey (CAS) to determine the point value of the measurement items of the JAMRIS-SIJ. Each CAS survey question asked the expert to compare two hypothetical patient profiles, which were otherwise similar but different at two items at a time, and to select which item showed a more severe stage of inflammation or osteochondral damage. In addition, experts ranked 14 JAMRIS-SIJ grade only or image + grade patient vignettes while blinded to the CAS-derived weights. The validity of the weighted JAMRIS-SIJ was tested by comparing the expert CAS-weighted score and the image + grade ranking method. Seventeen experts completed the CAS (11 radiologists and 6 rheumatologists). Considering the point value for inflammation domain items, osteitis (24.7%) and bone marrow edema (24.3%) had higher group-averaged percentage weights compared to inflammation in erosion cavity (16.9%), joint space enhancement (13.1%), joint space fluid (9.1%), capsulitis (7.3%), and enthesitis (4.6%). Similarly, concerning the damage domain, ankylosis (41.3%) and erosion (25.1%) showed higher group-averaged weights compared to backfill (13.9%), sclerosis (10.7%), and fat metaplasia lesion (9.1%). The Spearman correlation coefficients of the CAS-weighted vignette order and unweighted JAMRIS-SIJ grade only order vignettes for all experts were 0.79 for inflammation and 0.80 for damage. The correlations of image vignettes among imaging experts to CAS were 0.75 for inflammation and 0.90 for damage. The multicriteria decision analysis identified differences in relative weights among the JAMRIS-SIJ measurement items. The determination of the relative weights provided expert-driven score scaling and face validity for the JAMRIS-SIJ, enabling the future evaluation of its longitudinal construct validity.
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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 | 0.011 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".