How to Identify and Monitor Axial and Peripheral Psoriatic Arthritis by Magnetic Resonance Imaging
Bibliographic record
Abstract
Psoriatic arthritis (PsA) is characterized by a spectrum of clinical manifestations. Magnetic resonance imaging (MRI) is a crucial tool in elucidating inflammatory and structural lesions associated with both peripheral and axial forms of the disease. The implementation of standardized definitions and scoring systems for active and structural MRI lesions facilitates a rigorous evaluation of axial and peripheral joint involvement and enthesitis in patients with PsA. Further, the emerging potential of whole-body MRI techniques shows promise in differentiating treatment effects. The annual MRI workshop, held at the Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) 2024 meeting in Seattle, Washington, USA, aimed to underscore the significant role of MRI in the comprehensive assessment of PsA manifestations. Through the presentation of interactive case studies, the workshop illustrated the practical applications of MRI in the clinical management of individuals with PsA, enhancing understanding of its diagnostic capabilities and highlighting its contributions to treatment strategies.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.006 |
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".