Report of the IDEOM Meeting Adjacent to the GRAPPA 2024 Annual Meeting
Bibliographic record
Abstract
The International Dermatology Outcome Measures (IDEOM) organization presented updates on its patient-reported outcome measures (PROMs) for psoriasis (PsO), psoriatic arthritis (PsA), and other immune-mediated skin diseases at the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) 2024 annual meeting. The Hidradenitis Suppurativa working group reported on the IDEOM Musculoskeletal Questionnaire (MSK-Q), a PROM for MSK manifestations of psoriatic disease. Advances in PsA screening included integrating the Psoriasis Epidemiology Screening Tool (PEST) and 12-item Psoriatic Arthritis Impact of Disease (PsAID-12) questionnaires into the Epic electronic health record system to streamline detection and management of emerging PsA cases. The Connective Tissue Disease working group discussed upcoming trials and tools for addressing significant unmet needs in cutaneous lupus erythematosus. Finally, the Patient Satisfaction working group provided updates on the 7-item Dermatology Treatment Satisfaction Instrument (DermSat-7) and DermSat-11 for clinical trials and real-world studies. The DermSat-7 has been validated in a multicenter study of patients with PsO, whereas the DermSat-11 is currently undergoing validation. IDEOM continues to work to significantly improve patient outcomes and satisfaction in dermatology.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.051 | 0.018 |
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".