The effects of cannabis on mind-wandering
Bibliographic record
Abstract
To examine the effects of cannabis on mind-wandering, regular cannabis smokers of legally purchased pre-rolls took part in a three-session remote study. In each 30-min session participants completed three blocks of an attention task in which they pressed the spacebar in time with a metronome tone (the Metronome Response Task), and intermittently reported their levels of spontaneous and deliberate mind-wandering. Performance on the Metronome Response Task was indexed through response time variability, with greater response variability indicating poorer performance. Following an initial 'baseline' block, participants were instructed to mind-wander either 20 % or 80 % of the time in the second and third blocks (counterbalanced). Critically, the first and third sessions were scheduled on days of planned abstention while the second session immediately followed the (planned) use of cannabis (an ABA design). In the baseline blocks we found that cannabis use is associated with a large increase in spontaneous mind-wandering, a smaller increase in deliberate mind-wandering, and impaired task performance. When participants were instructed to mind-wander 20 % or 80 % of the time, cannabis use reduced instruction-related changes in deliberate mind-wandering and task performance, suggesting an impairment of the regulation of mind-wandering.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".