Bibliographic record
Abstract
Cannabis is an excellent natural source of fiber and various bioactive cannabinoids. So far, at least 120 cannabinoids have been identified, and more novel cannabinoids are gradually being unveiled by detailed cannabis studies. However, cannabinoids in both natural and isolated forms are especially vulnerable to oxygen, heat, and light. Therefore, a diversity of cannabinoids is associated with their chemical instability to a large extent. The research status of structural conversion of cannabinoids is introduced. On the other hand, the use of drug-type cannabis and the phytocannabinoids thereof has been rapidly popularized and plays an indispensable role in both medical therapy and daily recreation. The recent legalization of edible cannabis further extends its application into the food industry. The varieties of legal edible cannabis products in the current commercial market are relatively monotonous due to rigorous restrictions under the framework of Cannabis Regulations and infancy of novel developments. Meanwhile, patents/studies related to the safety and quality assurance systems of cannabis edibles are still rare and need to be developed. Furthermore, along with cannabinoids, many phytochemicals such as flavonoids, lignans, terpenoids, and polysaccharides exist in the cannabis matrix, and these may exhibit prebiotic/probiotic properties and improve the composition of the gut microbiome. During metabolism and excretion, the bioactive phytochemicals of cannabis, mostly the cannabinoids, may be structurally modified during enterohepatic detoxification and gut fermentation. However, the potential adverse effects of both acute and chronic exposure to cannabinoids and their vulnerable groups have been clearly recognized. Therefore, a comprehensive understanding of the chemistry, metabolism, toxicity, commercialization, and regulations regarding cannabinoid edibles is reviewed and updated in this contribution.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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 | 0.001 |
| 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".