Report of the Skin Research Workgroups From the IDEOM Breakout at the GRAPPA 2022 Annual Meeting
Bibliographic record
Abstract
The International Dermatology Outcome Measures (IDEOM) organization presented an update on its progress related to patient-centered outcome measures for psoriasis (PsO) and psoriatic arthritis (PsA) at the 2022 annual meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA). The Musculoskeletal (MSK) Symptoms working group presented an update on the development of the IDEOM Musculoskeletal Questionnaire (IDEOM MSK-Q). The IDEOM MSK-Q is a patient-reported outcome measure intended to capture MSK symptoms and describe their intensity and impact on health-related quality of life in patients with psoriatic disease. IDEOM also presented the progress of the integration of the Psoriasis Epidemiology Screening Tool (PEST) and Psoriatic Arthritis Impact of Disease (PsAID) questionnaires into the Epic electronic health record system. This will allow for automated PsA screening and symptom measurement in the hopes of improving disease detection and treat-to-target strategies. The Treatment Satisfaction working group discussed the development of the DermSat-7, a 7-item treatment satisfaction questionnaire specific for dermatological conditions. The DermSat-7 is currently being validated in a multicenter study of patients with PsO.
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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 | 0.035 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.029 | 0.011 |
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".