Prologue: 2015 Annual Meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA)
Bibliographic record
Abstract
The 2015 Annual Meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) was held in Stockholm, Sweden, and attended by rheumatologists, dermatologists, and representatives of biopharmaceutical companies and patient groups. In this prologue, we introduce the articles that summarize that meeting. As in previous years, GRAPPA members held a Trainees Symposium, providing an opportunity for trainees to discuss their research in psoriatic disease with experts in the field. Two dermatology sessions were held: an update on the International Dermatology Outcome Measures group; and a description of a new tool, the Comprehensive Assessment of the Psoriasis Patient, to more accurately assess the full burden of plaque psoriasis and its subtypes. Four distinct plenary sessions were held to update members on the status of the Outcome Measures in Rheumatology (OMERACT) initiative. GRAPPA's patient research partners discussed their 2 years of involvement in GRAPPA activities and were active in several sessions before and during the 2015 annual meeting. New work was presented toward developing a patient-reported instrument to measure flare in psoriatic disease, and the status of GRAPPA's multiple research and continuing education programs in psoriasis and PsA was summarized. Finally, a Presidential Round Table was held in which the past, current, and incoming presidents reflected on GRAPPA's history and provided insights about its future.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.199 | 0.124 |
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".