50th Year of Publication: Progress in Rheumatology During the 2010s
Bibliographic record
Abstract
In this edition of The Journal of Rheumatology , I will be bringing to your attention the following 6 articles from the 2010s that had, and continue to have, a significant impact in rheumatology. Although I usually choose 3 papers, I have chosen 6 that can be grouped into 3 categories. The first category has a single paper that describes a modification of the American College of Rheumatology (ACR) classification of fibromyalgia (FM),1 the second category contains 2 papers on the use of the internet and social media in rheumatology,2,3 and the third contains 3 papers on long-term outcome studies in rheumatoid arthritis (RA).4-6 The first paper I wish to bring to your attention is “Fibromyalgia criteria and severity scales for clinical and epidemiological studies: a modification of the ACR Preliminary Diagnostic Criteria for Fibromyalgia” by Wolfe et al. … Address correspondence to Dr. E.D. Silverman, Editor-in-Chief, The Journal of Rheumatology, 365 Bloor Street East, Suite 901, Toronto, ON M4W 3L4, Canada. Email: esilverman{at}jrheum.com.
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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.011 | 0.014 |
| Insufficient payload (model declined to judge) | 0.033 | 0.030 |
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".