Understanding, diagnosing, and treating Myalgic encephalomyelitis/chronic fatigue syndrome – State of the art: Report of the 2nd international meeting at the Charité Fatigue Center
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a devastating disease affecting millions of people worldwide. Due to the 2019 pandemic of coronavirus disease (COVID-19), we are facing a significant increase of ME/CFS prevalence. On May 11th to 12th, 2023, the second international ME/CFS conference of the Charité Fatigue Center was held in Berlin, Germany, focusing on pathomechanisms, diagnosis, and treatment. During the two-day conference, more than 100 researchers from various research fields met on-site and over 700 attendees participated online to discuss the state of the art and novel findings in this field. Key topics from the conference included: the role of the immune system, dysfunction of endothelial and autonomic nervous system, and viral reactivation. Furthermore, there were presentations on innovative diagnostic measures and assessments for this complex disease, cutting-edge treatment approaches, and clinical studies. Despite the increased public attention due to the COVID-19 pandemic, the subsequent rise of Long COVID-19 cases, and the rise of funding opportunities to unravel the pathomechanisms underlying ME/CFS, this severe disease remains highly underresearched. Future adequately funded research efforts are needed to further explore the disease etiology and to identify diagnostic markers and targeted therapies.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it