GRAPPA 2024 Meeting: Advances in Psoriatic Disease Research From Pilot Grant Awardees
Bibliographic record
Abstract
Prioritizing and supporting trainee research in psoriatic disease (PsD) is a cornerstone of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA). Each year, trainees and junior faculty are invited to submit proposals to GRAPPA to fund pilot research projects related to psoriasis or psoriatic arthritis. Projects can be in any of the following 4 categories: clinical science, translational science, basic science research, or combined PsD. GRAPPA remains committed to showcasing the trainee research supported by these grants at the annual meeting. The GRAPPA 2024 annual meeting and trainee symposium was held in Seattle, Washington, USA; a meeting highlight was the session dedicated to the pilot research grant projects led by trainees and faculty. This year, 27 submissions were received from 14 countries across North America, Europe, and Asia. Compared to prior years, an updated grant review process enhanced efficiency and created more opportunities for conversation among evaluators. A panel of 14 GRAPPA reviewers assessed the submissions, ultimately selecting 4 projects for funding. This meeting report aims to summarize the 2024 pilot research grant recipients and the project results from past grant recipients.
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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 | 0.090 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.031 | 0.017 |
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".