Can a consensus occur on a research case definition for ME/CFS?
Bibliographic record
Abstract
Introduction: Many controversies have emerged around developing a consensus on a research case definition for ME and ME/CFS. To determine if there might be a consensus among patients, healthcare workers, and researchers, a brief questionnaire was distributed to an international group of patients to assess key issues involving ME and ME/CFS case definitions.Method: Respondents were asked questions about core symptoms and other critical case definition issues.Results: Overall, post-exertional malaise, cognitive impairment, fatigue, and unrefreshing sleep were the most endorsed core symptoms with at least 80% consensus among participants. Considerable support occurred for the ME-ICC (Myalgic Encephalomyelitis-International Consensus Criteria) and the Canadian Consensus Criteria (CCC), whereas the Fukuda Criteria received the least support. Items rated as important for a research case definition included the severity of the illness, onset type, duration of illness, illness course, exclusions, and comorbidities.Conclusions: The implications of these findings for developing a consensus on research case definition criteria are discussed.
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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 | 0.488 | 0.669 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.006 |
| Science and technology studies | 0.007 | 0.020 |
| Scholarly communication | 0.015 | 0.027 |
| Open science | 0.013 | 0.020 |
| Research integrity | 0.014 | 0.014 |
| Insufficient payload (model declined to judge) | 0.005 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".