Progress in Measurement Instruments for Acute and Chronic Gout Studies
Bibliographic record
Abstract
Consensus exercises have identified and prioritized domains of measurement for studies in acute and chronic gout. In parallel, the technical properties of instruments for measurement in many of these domains have been assessed, with the main objective to consider the instruments in the context of the OMERACT filter of truth, discrimination, and feasibility. These data were presented and discussed at OMERACT 9 in the gout workshop, in breakout groups, and at informal meetings of the gout group. In acute gout, instruments for domains of pain, joint swelling, joint tenderness, and patient and physician global assessment have been assessed. In chronic gout, some validation exercises have been performed in instruments for domains serum urate, tophus measurement, health-related quality of life (HRQOL). In voting at OMERACT 9, the Medical Outcomes Study Short-Form 36 was endorsed as a valid instrument for measurement of HRQOL. Methods of tophus measurement were considered to have met some criteria of the OMERACT filter, but these require further work, particularly regarding sensitivity to change over shorter time periods. Priorities for future research include measurement of joint inflammation in acute gout and disability in acute and chronic gout.
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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 | 0.525 | 0.446 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".