A survey of veterinary student attitudes concerning whether marijuana could have therapeutic value for animals
Bibliographic record
Abstract
Marijuana is increasingly recognized for its therapeutic value in human medicine. Although most veterinary research to date has been concerned with marijuana toxicity, there is some interest in the potential therapeutic value of marijuana in veterinary medicine. With the recent legalization of marijuana for recreational use in Canada in October 2018, there is a need for veterinarians and veterinary students to be in a position to address client questions and concerns on this topic. We distributed a questionnaire to current veterinary students at the Ontario Veterinary College in Guelph, Ontario, to determine their attitude(s) towards marijuana as a potential therapeutic agent in animals. The overall response rate for the questionnaire was 43.5% (207/476). Most students felt that marijuana has potential therapeutic value in animals (53.6%; 111/207), fewer were unsure (38.6%; 80/207), and a small number of students felt that marijuana does not have potential therapeutic value in animals (7.7%; 16/207). Data generated by this questionnaire identified an important distinction between two major active compounds found in marijuana: cannabidiol (CBD) and tetrahydrocannabinol (THC). Potential barriers to use in veterinary practice were also identified, including stigma and toxicity. Finally, many respondents showed an awareness of the limited scientific research regarding the safety and efficacy of marijuana in animals. Until a body of scientific literature on marijuana in animals becomes available, veterinarians may benefit from having an awareness of the different physiological and pharmacokinetic effects produced by different strains (including any adverse effects, and half-life), and a general understanding of current therapeutic applications of marijuana in humans.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".