Imaging as an Outcome Measure in Gout Studies: Report from the OMERACT Gout Working Group
Bibliographic record
Abstract
OBJECTIVE: The gout working group at the Outcome Measures in Rheumatology (OMERACT) 12 meeting in 2014 aimed to determine which imaging modalities show the most promise for use as measurement instruments for outcomes in studies of people with chronic gout and to identify the key foci for future research about the performance of these imaging techniques with respect to the OMERACT filter 2.0. METHODS: During the gout session, a systematic literature review of the data addressing imaging modalities including plain radiography (XR), conventional computed tomography (CT), dual-energy computed tomography (DECT), magnetic resonance imaging (MRI), and ultrasound (US) and the fulfillment of the OMERACT filter 2.0 was presented. RESULTS: The working group identified 3 relevant domains for imaging in gout studies: urate deposition (tophus burden), joint inflammation, and structural joint damage. CONCLUSION: The working group prioritized gaps in the data and identified a research agenda.
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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 | 0.010 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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".