Bibliographic record
Abstract
As I mentioned in my editorial appearing in this year’s January issue, 2023 is the 50th anniversary of the publication of The Journal of Rheumatology .1 Over the course of the year, I will be highlighting articles published in The Journal that have been important publications in terms of their influence on the practice of rheumatology. In this month’s edition, I have selected 3 articles published in The Journal during the 1980s that I feel were, and continue to be, important to rheumatologists and therefore worthy of a second look by you, the readers. These are (1) a validation study of WOMAC by Bellamy et al2; (2) a description of 9 patients with primary antiphospholipid syndrome by Alarcon-Segovia and Sanchez-Guerrero3; and (3) a study introducing the Arthritis Helplessness Index by Nicassio et al.4 The article … 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 | 0.017 | 0.061 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.017 | 0.010 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.015 | 0.026 |
| Insufficient payload (model declined to judge) | 0.014 | 0.012 |
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".