Prologue: 2014 Annual Meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA)
Bibliographic record
Abstract
The 2014 Annual Meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) was held in New York, New York, USA, and attended by rheumatologists, dermatologists, and representatives of biopharmaceutical companies and patient groups. Summaries of presentations at that meeting are introduced, including the GRAPPA-organized Fellows Symposium adjacent to the 2014 Swiss Psoriasis Day in Geneva. At the GRAPPA meeting itself, a Trainees Symposium was organized for rheumatology fellows and dermatology residents to present their research work; several patient research partners (PRP) organized Building Bridges, a session of interactive dialogue regarding the roles and responsibilities of PRP and researchers participating in working groups at GRAPPA and elsewhere; and 5 dermatology sessions were held to report on the international dermatology outcome measures group. Among the meeting topics were dermatologists’ management of psoriatic arthritis (PsA); the unmet need for a comprehensive assessment tool for psoriasis; the Psoriasis Symptom Inventory; and the importance of treat-to-target strategies for managing psoriasis. Other presentations included an update of GRAPPA’s research initiative to develop evidence-based criteria to identify inflammatory arthritis, enthesitis, dactylitis, and spondylitis; the utility of magnetic resonance imaging in PsA; a review of the PsA working group at OMERACT (Outcome Measures in Rheumatology); and updates on several GRAPPA educational projects. Considerable time was allotted to discussions of GRAPPA’s efforts to update its treatment guidelines for PsA.
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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 | 0.003 | 0.006 |
| 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 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.211 | 0.128 |
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".