The microbiological testing regulations for cannabis products in Canada: Are they enough from food safety and public health point of view?
Bibliographic record
Abstract
Canada has recently legalised cannabis for its production, sale and usage in various ways viz. medicinal, recreational and edible. The Access to Cannabis for Medical Purposes Regulations (ACMPR) suggests that the microbial and chemical contaminants of fresh or dried marihuana or cannabis must be as per Schedule B of the Food and Drugs Act. It prescribes the testing for total aerobic count (TAC), yeast and mould count (YMC), Salmonella counts, Escherichia coli counts and total coliforms. The recent study revealed that there are 13 endophytic bacterial isolates and 30 endophytic fungal isolates which are harboured by cannabis. Though all phytopathogens may not infect humans, except perhaps immunocompromised individuals; it is obvious that present microbiological testing may not be enough to detect the plethora of microorganisms. Also, the testing for viruses like hepatitis A and hepatitis B are not provisioned by regulation though there are reports of their outbreaks and there is no provision for testing bacteria like Clostridium botulinum and Listeria monocytogenes. The present traditional culture-based testing methods may not be adequate in identifying food safety risks.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".