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In this paper, I present a model, SimSemilla, that explores at a high level of abstraction
what we do and don’t know about how cannabis use translates into harms. The model allows
us to explore plausible implications of variations in assumptions (e.g., “potency
doesn’t matter because users simply titrate their doses”, “heavy users are at greatest
risk,” “heavy users are more experienced and more tolerant,” etc.) Because the model
is explicit, it calls attention to the importance of many parameters for which better
measurement is woefully needed.