Synthetic Opioids, (re)Emerging Problem in Europe and North America
Bibliographic record
Abstract
I would like to draw the reader´s attention to group of synthetic opioids, which have been increasingly appearing or re-emerging during the last few years on the black drug markets in many European countries, the USA, Canada and elsewhere. Newly encouraged interest in synthetic opioids has been observed for last 6-7 years and recently has grown intensively. Increasing number of European countries (Germany, Bulgaria, Slovakia, Czech Republic etc.) have reported abuse of fentanyl (Janssen, 1962), which so far has been rather limited to Estonia (Fentanyl in Europe, 2012; Mounteney, 2015), fentanylrelated intoxications and deaths have markedly increased recently (to hundreds) in the USA (NIDA, 2015) and Canada (CCNDU Bulletin, 2014). Also the spectrum of different structures of synthetic opioids on the black market has significantly risen and many of these substances are already associated with serious or fatal overdoses (EMCDDA, 2009-12; European Drug Report, 2013-15).
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".