The abuse potential of the synthetic cannabinoid nabilone
Bibliographic record
Abstract
AIM: Nabilone is a synthetic cannabinoid prescription drug approved in Canada since 1981 to treat chemotherapy-induced nausea and vomiting. In recent years, off-label use of nabilone for chronic pain management has increased, and physicians have begun to express concerns about nabilone becoming a drug of abuse. This study evaluates the evidence for abuse of nabilone, which is currently ill-defined. STUDY DESIGN: Scientific literature, popular press and internet databases were searched extensively for evidence of nabilone abuse. Focused interviews with medical professionals and law enforcement agencies across Canada were also conducted. FINDINGS: The scientific literature and popular press reviews found very little reference to nabilone abuse. Nabilone is perceived to produce more undesirable side effects, to have a longer onset of action and to be more expensive than smoked cannabis. The internet review revealed rare and isolated instances of recreational use of nabilone. The database review yielded little evidence of nabilone abuse, although nabilone seizures and thefts have occurred in Canada in the past few years, especially in Ontario. Most law enforcement officers reported no instances of nabilone abuse or diversion, and the drug has no known street value. Medical professionals reported that nabilone is not perceived to be a matter of concern with respect to its abuse potential. CONCLUSIONS: Reports of nabilone abuse are extremely rare. However, follow-up of patients using nabilone for therapeutic purposes is prudent and should include assessment of tolerance and dependence. Prospective studies are also needed to definitively address the issue of nabilone abuse.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".