Cannabis use in pregnancy: a harm reduction approach is needed with a focus on prevention and positive intervention
Bibliographic record
Abstract
Commentary on: Corsi DJ, Walsh L, Weiss D, et al . Association between self-reported prenatal cannabis use and maternal, perinatal, and neonatal outcomes. JAMA 2019;322:145–52. Cannabis use is increasing in North America among young people aged 15 to 24 years including women who are pregnant. With recent legalisation in multiple jurisdictions, and discussion about its medical benefits for a variety of conditions, it is anticipated that cannabis use may further increase during pregnancy. Cannabinoids can readily cross the placenta and may disrupt the complex fetal endogenous cannabinoid signalling system. This may lead to adverse pregnancy outcomes. Previous studies have varied in methodology and treatment of confounding …
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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 | 0.006 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.003 | 0.008 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.060 | 0.060 |
| Insufficient payload (model declined to judge) | 0.014 | 0.008 |
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".