The effects of vaped cannabis on the severity of naloxone-precipitated opioid withdrawal.
Bibliographic record
Abstract
50) withdrawal using the Clinical Opiate Withdrawal Scale (COWS, range = 0-48) as the primary dependent measure. Evaluating the safety of this drug combination was the secondary aim, assessed using vital signs. Before a major methodological redesign, a single participant (male, 52) with opioid use disorder completed testing. The ∼4-week inpatient study began with stabilization on oral morphine (120 mg/day). During testing, the following dose combinations of vaped cannabis (V-CB) and intranasal naloxone (IN-NLX) were tested: (a) IN-NLX 0.0 mg + V-CB 25.0 mg, (b) IN-NLX 4.0 mg + V-CB 0.0 mg, (c) IN-NLX 0.0 mg + V-CB 12.5 mg, (d) IN-NLX 4.0 mg + V-CB 12.5 mg, (e) IN-NLX 0.0 mg + V-CB 0.0 mg, and (f) IN-NLX 4.0 mg + V-CB 25.0 mg. Naloxone alone resulted in a COWS score of 22 at T+30. CB pretreatment (12.5 mg and 25.0 mg) reduced COWS scores at T+30 to 17 and 14, respectively. Active NLX and V-CB administered in combination resulted in elevated heart rate and blood pressure, though not to a greater extent than NLX alone. This study found that the addition of a cannabinoid reduced the severity of NLX-precipitated withdrawal and supported the continued investigation into combined NLX + cannabinoid formulations as overdose reversal agents. (PsycInfo Database Record (c) 2026 APA, all rights reserved).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".