Multiple Fatalities Involving a New Designer Drug: Para-Methyl-4-Methylaminorex
Bibliographic record
Abstract
In recent years, the pace at which new psychoactive substances (NPS) have emerged has accelerated considerably. The European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) reported that between 2005 and 2011, 164 NPS were formally notified through the early warning system. While 49 NPS were notified in 2011 alone (1), a further increase of 73 NPS has been observed for 2012 (2). Many of these substances are sold in so-called head shops or over the internet and are often described as “not for human consumption” to avoid regulatory difficulties. The commercial availability of these substances may differ between countries but appears to be influenced by their control status, which means that there may be a tendency to change the product catalog of available substances by introducing new analogs that may not be captured by legislative control. The toxicity of these new substances is often poorly understood, although many of the compounds appear to have psychoactive and psychostimulant properties in humans. However, fatal toxicity has been attributed to many of these compounds as well, either with or without the presence of other drugs (3). A cluster of deaths in Northern Ireland occurred during 2013 and several of these were associated with the police seizure of tablet items (“Speckled Cherry” and “Speckled Cross” motifs).
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.028 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".