Bibliographic record
Abstract
PURPOSE OF REVIEW: The endocannabinoid system affects several physiological functions. A family of endocannabinoid receptors is susceptible to cannabis constituents. Cannabis is widely used in our society and following its recent legalization in Canada, we focus on how exposure to cannabis and pharmacologic cannabinoid receptor type 1 (CB1) inhibition affect lipoprotein levels. RECENT FINDINGS: Several groups have reported that exposure to cannabis does not increase weight despite the marked increase in caloric intake. In observational studies, the effect of smoked cannabis exposure on plasma lipids is variable. Some studies in specific patient populations with longer exposure to cannabis seemed to identify slightly more favorable lipoprotein profiles in the exposed group. Several larger controlled clinical trials using orally administered rimonabant, a CB1 receptor antagonist, have consistently shown relative improvements in weight and plasma levels of triglyceride and high-density lipoprotein cholesterol among patients receiving the treatment. SUMMARY: The widely variable findings on the relationship of cannabis in various forms with plasma lipids preclude any definitive conclusions. Cannabis has complex effects on the cardiovascular system and its effects on lipid profile must be considered in this overall context. Further properly controlled research is required to better understand this topic.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".