Prologue: 2011 Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA)
Bibliographic record
Abstract
The 2011 Annual Meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) was held in July 2011 in Naples, Italy, and attended by rheumatologists, dermatologists, and representatives of biopharmaceutical companies and patient groups from around the world. The meeting began with a trainee symposium, where 25 rheumatology fellows and dermatology residents presented their original research work. Presentations and discussions by GRAPPA members during the remaining 2-day meeting included a 2-part discussion of the status of psoriatic disease biomarker research, summaries of the GRAPPA Composite Exercise and the GRAPPA video projects, a contribution from Italian members on their psoriasis and PsA projects, a lengthy discussion of research and collaborative initiatives from GRAPPA dermatologists, updates on ultrasound imaging in psoriatic disease and on plans to define inflammatory musculoskeletal disease, a presentation of the results of a small study of psoriasis and PsA in aboriginal people of Peru, and a review of global education and partnering opportunities. Introductions to these discussions are included in this prologue.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.162 | 0.092 |
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".