Young-GRAPPA 2024: Progress, Achievements, and Strategic Developments
Bibliographic record
Abstract
The Young Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (Y-GRAPPA) was established in 2021. As of July 2024, the group consists of 152 members, featuring a balanced gender distribution and a 70/30 split between rheumatology and dermatology specialties. In the last year, Y-GRAPPA updated its major project-the GRAPPA slide library-to include translations in 5 new languages, continued to publish the "Do Not Miss" newsletters, and presented "Virtual Highlights" for major international conferences (American Academy of Dermatology [AAD] annual meeting, European Alliance of Associations for Rheumatology [EULAR] annual congress, European Academy of Dermatology and Venereology [EADV] congress, and American College of Rheumatology [ACR] Convergence). Presently, Y-GRAPPA is boosting social media presence and refining its organizational structure and activities. This includes restructuring committees with new leaders to each focus on specific objectives, streamlined leadership, and proactive member recruitment and engagement. The key objective of Y-GRAPPA remains to ensure active participation in all GRAPPA activities through collaboration and communication between Y-GRAPPA and senior GRAPPA members.
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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 | 0.023 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.010 |
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".