Bibliographic record
Abstract
OBJECTIVE: To examine the nature and degree of self-reported disability in patients with chronic fatigue syndrome (CFS) and its associated conditions, fibromyalgia (FM) and subsyndromal fatigue (CF), compared with a chronically fatiguing but unrelated medical condition (MED). METHODS: Six hundred and thirty patients evaluated at the University of Washington Chronic Fatigue Clinic were sent questionnaires asking them to identify the financial, occupational, and personal consequences of their fatiguing illness. Thorough medical evaluations had previously applied accepted criteria for defining CFS, FM, and CF. RESULTS: The FM groups (those with and without CFS) were among the least employed. Likewise, the FM and CFS groups, more frequently than the other groups, endorsed loss of material possessions (such as car), loss of job, and loss of support by friends and family, as well as recreational activities as a result of their fatiguing illness. There were no reliable differences between groups in use of disability benefits. CONCLUSION: There is substantial illness-related disability among those evaluated at a specialized chronic fatigue clinic. Those reporting the most pervasive disability met criteria for FM either alone or in conjunction with CFS. Employers and personal relations of patients with chronic fatigue should make a greater effort to accommodate the illness-related limitations of these conditions, especially for those with FM and CFS.
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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".