Pain Res Manag Vol 19 No 6 November/December 2014 293 Fibromyalgia and disability adjudication: no simple solutions to a complex problem
Bibliographic record
Abstract
There is a general consensus that fibromyalgia (FM) is frequently associated with severe impairment of function leading to inability to engage in gainful employment. Data supporting this view are derived from various populations and geographical locations. In a study involving patients at six rheumatology centres in the United States, Wolfe et al (1) found that 26.5 % were receiving disability pay-ments. Winkelmann et al (2) surveyed 299 patients with FM recruited from physician offices in France and Germany; approximately 26 % of the French and 28 % of the German patients reported early retirement or unemployment due to FM. In a Scottish centre, 46.8 % of patients with FM reported that that they had lost their job because of this con-dition, compared with 14.1 % of those without FM (3). In a Canadian community study, 26 % of FM cases were receiving some form of dis-ability payment (4). Furthermore, individuals with FM who remain in the work force have a higher rate of absenteeism and a lower work output than workers without FM (5).
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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.024 | 0.009 |
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".