Advancing Stiffness Measurement in Rheumatic Disease: Report from the Stiffness Special Interest Group at OMERACT 2018
Bibliographic record
Abstract
OBJECTIVE: To improve measurement of stiffness in rheumatic disease. METHODS: Data presented included (1) 2 qualitative projects, (2) the rheumatoid arthritis (RA) stiffness patient-reported outcome measure (RAST), and (3) 3 items assessing stiffness severity, duration, and interference. RESULTS: Stiffness is multidimensional and includes aspects of stiffness experience such as duration, severity, and effect. Stiffness items showed construct validity in RA. Further efforts are required to develop an instrument that will be taken through the Outcome Measures in Rheumatology (OMERACT) Filter 2.1 for instrument selection. CONCLUSION: The research agenda for the group includes domain content voting for individual diseases, and development of stiffness item banks and disease-specific short forms.
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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 | 0.020 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".