A patient with epilepsy charged with kidnapping, unlawful confinement, and assault causing bodily harm after seizures: Deficiencies in the legal system
Bibliographic record
Abstract
We report the rare case of a 34-year-old right-handed male who had drug-resistant epilepsy associated with a frontal cavernoma since the age of 13 who was convicted of criminal charges related to seizures. When he was 32 years old, he had a focal seizure with impaired awareness and then he tried to grab a 7-year-old girl who was in a car coming out from a dance class. He was arrested and taken to the police station. Later that day, the patient was being interrogated by a police officer when he had a hypermotor seizure at the end of the interview. He punched the policeman leading to multiple charges laid, including kidnapping, unlawful confinement, and assault causing bodily harm. He remained in jail for the next year and a half. During this time, he had epilepsy surgery for resection of the cavernoma. The patient was rendered seizure-free after resection of the cavernoma for one-year. Due to the occurrence of seizures before the alleged "kidnapping" and based upon his interview with the policeman, the patient was acquitted from all legal charges. We review available cases of non-homicidal criminality with a legal outcome in this article.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".