A young woman with multiple acyl-CoA dehydrogenase deficiency (MADD)
Bibliographic record
Abstract
A 31-year-old female hairdresser whose parents were first degree cousins complained of episodic attacks of headache, vomiting, and dizziness for the past eight years after an uneventful childhood and adolescence. Four years ago, she developed progressive weakness, muscle pain and difficulties walking and lifting her arms that she could not work in her profession anymore. She lost hair, weight and became amenorrhoic. Finally, her muscle weakness required intensive care. Early on her CK was mildly elevated to 237 U/l (normal < 167), but later to 900 and 1800. By MRI, skeletal muscles showed minimal contrast enhancement. The clinically suspected diagnosis of myositis prompted repeated muscle biopsies, which disclosed non-specific myopathic changes, scattered necrotic muscle fibers without inflammation, protein aggregation, or vacuolation by light microscopy, but abnormally structured mitochondria with inclusions by electron microscopy, and treatment with steroids without any clinical improvement. A panel of 1131 mitochondrial genes revealed a homozygous mutation in the ETFDH gene. LEARNING OBJECTIVES This presentation will enable the learner to: 1. Discuss MADD as a mitochondrial and lipid storage disease 2. Recognize the myopathology of MADD
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".