Challenges in the Diagnosis and Assessment of Psoriatic Arthritis
Bibliographic record
Abstract
Each year, the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) holds a trainee symposium adjacent to the GRAPPA annual meeting. The target audience for this meeting includes trainees in rheumatology, dermatology, and related fields. The 2021 GRAPPA Trainee Symposium focused on challenges in the diagnosis and assessment of psoriatic arthritis (PsA). During the meeting, speakers focused on identification of psoriasis (PsO), the differential diagnosis for both PsO and PsA, diagnostic errors and pitfalls, physical examination in PsA, patient-reported outcomes and composite measures in the assessment of PsA, and the patient perspective on diagnosis and assessment, followed by a panel discussion. This paper summarizes the content discussed at the meeting.
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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 | 0.081 | 0.139 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.006 | 0.017 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".