The Importance of Patient Input into Development of Outcomes in Idiopathic Inflammatory Myopathy
Bibliographic record
Abstract
In this issue of The Journal , Mecoli, et al report the results of an international survey of healthcare providers and patients with idiopathic inflammatory myopathy (IIM) to examine and compare perceptions of disease features and effects1. This work is part of an overall program to develop patient-reported outcomes in IIM, given that it is recognized that these have not been well studied to date2. This study raises a number of important issues and has implications for future research. This work follows the procedures described by the Outcome Measures in Rheumatoid Arthritis Clinical Trials (OMERACT) initiative. OMERACT is the acronym for an international, informally organized network initiated in 1992, which aimed at improving outcome measurement in rheumatology3. Using this methodology confers a number of important strengths to this work. It contributes to transparency by explicitly describing the process by which decisions are made throughout the process. It requires that … Address correspondence to Dr. A.M. Huber. IWK Health Centre, 5850 University Ave., Halifax, Nova Scotia B3K 6R8, Canada. E-mail: adam.huber{at}iwk.nshealth.ca
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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 | 0.016 | 0.086 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".