A fatal motor vehicle collision involving multiple novel psychoactive substances
Bibliographic record
Abstract
Novel psychoactive substances comprise a number of chemically diverse substances that have emerged in the illicit market over the past decade and continue to be readily available. These compounds have been considered “legal alternatives” for typical drugs of abuse and often share similar pharmacological profiles. Presented herein is a case from the United States of a 29-year-old male with no known past medical history that was suspected of impaired driving while traveling at a high rate of speed. The vehicle stopped when the decedent lost control and collided with a guardrail. The decedent was ejected and found lying near the guardrail with extensive blunt force trauma and was pronounced deceased at the scene. Initial screening of the decedent’s cardiac blood revealed 3-methoxy-PCP, butylone, delorazepam, and N-ethylpentylone. Further testing provided by an outside reference laboratory additionally confirmed 3-fluorophenmetrazine, diclazepam, etizolam, and fluoroamphetamine. Testing of scene evidence revealed the presence of 2-fluoro-deschloroketamine, butylone, diclazepam, etizolam, and N-ethylpentylone. The cause of death was attributed to an internal hemorrhage due to a laceration of the aortic root with multiple skeletal fractures resulting from blunt force trauma. The manner of death was accidental. The compounds detected in this case may have played a significant role in facilitating this fatal crash. This report documents a unique instance of poly-NPS use, and a discussion on the analytical and interpretive considerations commonly encountered when analyzing NPS is also presented.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| 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".