Is medical marijuana legalisation possible in Poland?
Bibliographic record
Abstract
OBJECTIVES: In some countries of the world it is legal to use plant-based marijuana for therapeutic purposes. When we had learned that 7,000 petitioners (including doctors) signed the petition to enable access to marijuana for patients in the Czech Republic, we decided to examine the knowledge about marijuana's medical properties among Polish medical students. METHODS: Anonymous questionnaire study was conducted on a group of 181 of students of the last (sixth) year of medical school. RESULTS: It was demonstrated that students are not provided with sufficient information about therapeutic administration of plant-based marijuana during medical studies. The majority of interviewees mentioned only one indication for medical marijuana use. All students did not interchange medical conditions for which marijuana is used in 30 USA states or Canada. DISCUSSION: Marijuana smoking for medical purposes differs from recreational smoking, and its effect does not depend on occurrence of symptoms from the central nervous system. Few studies, that were carried out along with numerous previously unreported cases of patients, demonstrated that plant-derived marijuana had therapeutic effect on many diseases where conventional medicine was of no help. CONCLUSION: All doctors, including medical students, should receive more information about the therapeutic properties of marijuana.
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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 | 0.001 | 0.004 |
| 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 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".