Review of the Psoriatic Arthritis Working Group at OMERACT 12: A Report from the GRAPPA 2014 Annual Meeting
Bibliographic record
Abstract
At the 2014 annual meeting of the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA), the psoriatic arthritis (PsA) working group of OMERACT (Outcome Measures in Rheumatology) presented a review of the progress made at the OMERACT 12 meeting, held in 2014. Members of the PsA OMERACT working group presented work from the Patient Involvement in Outcome Measures for PsA initiative to improve the incorporation of patient research partners in PsA outcomes research, the results of discussions within the OMERACT breakout groups, and finally the voting results. The OMERACT 12 participants had endorsed the need to update the PsA core set according to the Filter 2.0 framework. The breakout group discussions identified potential opportunities for revising the core set, including consolidating existing redundancy within the core set, improving incorporation of the patient perspective, and including disease effects such as fatigue as a core criterion. GRAPPA members of the OMERACT working group now have a program of research to update the core set with the goal of seeking endorsement at OMERACT 13, to be held in 2016.
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 | 0.067 | 0.149 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".