Differentiation of the Clinical Features of Psoriatic Arthritis and Fibromyalgia
Bibliographic record
Abstract
To the Editor: I read with interest the article by Marchesoni, et al 1 in which the authors state that the features distinguishing fibromyalgia syndrome (FM) from psoriatic arthritis (PsA) were the number of FM-associated somatic symptoms and tender point count, not the Maastricht Ankylosing Spondylitis Enthesitis Score (MASES)2. But the alternative diagnostic criteria for FM, the American College of Rheumatology (ACR) 2010 criteria3, are based on patient self-assessment without any tender point count. On the other hand, there is an argument for the somatic symptoms of 41 items that are considered specific for FM4, but Marchesoni, et al considered them as confusing the … Address correspondence to Dr. Konno; E-mail: taiki{at}snow.plala.or.jp
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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 | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.014 | 0.015 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".