Toward a Sonographic Composite Index for Diagnosis in Psoriatic Arthritis: Highlights From the GRAPPA Ultrasound Workshop
Bibliographic record
Abstract
The ability to visualize musculoskeletal structures with high-resolution ultrasound is an asset to understanding the complexity of psoriatic arthritis (PsA). During the 2021 Annual Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) meeting, 3 topics were presented and discussed in the ultrasound workshop: (1) the progress on the Diagnostic Ultrasound Enthesitis Tool (DUET) project; (2) the sonographic evaluation of joints in PsA-GRAPPA joint project; and (3) extrasynovial lesions in PsA. The ultrasound group aims to develop sonographic tools that are feasible and can be used in standard care to diagnose PsA early. The discussions around these topics will shape the group's work toward developing a composite index to diagnose PsA early.
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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 | 0.034 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".