People With Myasthenia Are Getting Better, but Are They Doing Well?
Bibliographic record
Abstract
The natural history of myasthenia gravis (MG) has changed dramatically over the past century. Multiple studies have shown a steady decline in the proportion of deaths caused by MG.1 This is due in part to improved treatments but also to improved and earlier diagnosis. Greater capacity to diagnosis MG likely means that there are more people living with the disease than previously.2 Current statistics show that most people with myasthenia get better with treatment, with ≈10% to 15% of patients exhibiting refractory disease.3 However, the fact that most patients do better with treatment does not mean that most patients are doing well. In this edition of Neurology ®, Petersson et al.4 report the findings of a large cross-sectional survey of adults living with myasthenia in Sweden that indicates that half of participants reported dissatisfaction with disease control. This means that individuals do not experience enough symptom suppression to allow them to engage in meaningful activities.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.013 | 0.020 |
| Insufficient payload (model declined to judge) | 0.009 | 0.010 |
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".