Comment on “Fibromyalgia and Physical Trauma: The Concepts We Invent”
Bibliographic record
Abstract
To the Editor: It was with great interest that we read the review by Wolfe, et al 1 dealing with the issue of fibromyalgia (FM) and physical trauma. The authors of the paper consider and discuss FM and chronic widespread pain (CWP) as if they are identical. In fact, the authors claim that the 1990 American College of Rheumatology (ACR) FM criteria2 are obstacles to performing clinical and epidemiological research. We believe that in trained hands the performance of tender point count takes less time than it takes to complete the 2010 ACR FM preliminary criteria questionnaires3. This notion was expressed years ago: “All patients have multiple areas of local tenderness called ‘tender points’ that are easily identified … Address correspondence to Dr. R. Mader, Rheumatic Diseases Unit, Ha’Emek Medical Center, Afula 18101, Israel. E-mail: Mader_r{at}clalit.org.il
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 | 0.006 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.045 | 0.043 |
| Insufficient payload (model declined to judge) | 0.006 | 0.007 |
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".