National Association of Medical Examiners Position Paper: Recommendations for the Investigation and Certification of Deaths in People with Epilepsy
Bibliographic record
Abstract
Sudden unexpected death of an individual with epilepsy (SUDEP) can pose a challenge to death investigators, as most deaths are unwitnessed and the individual is commonly found dead in bed. Anatomic findings (e.g., tongue/lip bite) are commonly absent and of varying specificity, limiting the evidence to implicate epilepsy as a cause of or contributor to death. Thus, it is likely that death certificates significantly underrepresent the true number of deaths in which epilepsy was a factor. To address this, members of the National Association of Medical Examiners, North American SUDEP Registry, Epilepsy Foundation SUDEP Institute, American Epilepsy Society, and the Centers for Disease Control and Prevention convened an expert panel to generate evidence-based recommendations for the practice of death investigation and autopsy, toxicological analysis, interpretation of autopsy and toxicology findings, and death certification to improve the precision of death certificate data available for public health surveillance of epilepsy-related deaths. The recommendations provided in this paper are intended to assist medical examiners, coroners, and death investigators when a sudden, unexpected death in a person with epilepsy is encountered.
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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 | 0.030 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.006 | 0.003 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 0.015 |
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".