Strategies of intervention to limit the novel synthetic opioids (NSO) escalation in Europe
Bibliographic record
Abstract
October 9 th 2018 marked the entry into force of the EU-funded project JUSTSO (Analysis, knowledge dissemination, JUstice implementation and Special Testing of novel Synthetic Opioids) (1).The JUSTSO Project involves 10 European partners from Italy, Spain, Greece, Latvia, Germany.The project is aimed at studying Novel Synthetic Opioids (NSO), a class of psychoactive substances that mimic heroin and can be up to 10000 times more potent than heroin, being the cause of thousands of deaths in the US and Canada.NSO have been used to adulterate heroin, often taken by subjects made dependent on opioid pain killers.Given the growing use of opioid pain killers and NSO in Europe, the project intends to collect data on their diffusion and to develop effective intervention strategies to prevent their spread and to inform and educate the public in order to acquire a social awareness of their addiction liability and lethality.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".