The Sjögren's Working Group: The 2023 OMERACT meeting and provisional domain generation
Bibliographic record
Abstract
Sjögren's disease (SjD) is a systemic autoimmune exocrinopathy with key features of dryness, pain, and fatigue. SjD can affect any organ system with a variety of presentations across individuals. This heterogeneity is one of the major barriers for developing effective disease modifying treatments. Defining core disease domains comprising both specific clinical features and incorporating the patient experience is a critical first step to define this complex disease. The OMERACT SjD Working Group held its first international collaborative hybrid meeting in 2023, applying the OMERACT 2.2 filter toward identification of core domains. We accomplished our first goal, a scoping literature review that was presented at the Special Interest Group held in May 2023. Building on the domains identified in the scoping review, we uniquely deployed multidisciplinary experts as part of our collaborative team to generate a provisional domain list that captures SjD heterogeneity.
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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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.080 | 0.036 |
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".