Place du cannabis thérapeutique dans le traitement des douleurs chroniques, en route vers sa reconnaissance médicale ?
Bibliographic record
Abstract
The discovery of the endocannabinoid system in the 1990s has opened the way for medical cannabis. Three cannabinoid medicines are currently available in some countries for specific therapeutic indications: spastic pain of multiple sclerosis, chemotherapy-induced nausea and vomiting and anorexia in patients with HIV. The research progress and new therapeutic applications are growing, especially for chronic pain’s treatment. A large part of the population is affected with this pathology and cannabinoid’s use in chronic pain’s treatment has given important results in several preclinical and clinical studies. While in some countries such as Canada or United states, drugs derived from cannabis are available with a prescription in pharmacy for over 15 years, France appears to be lagging behind. However, French people say themselves to be ready to use cannabis-based medication if needed. These new treatments seem to be promising; however medical cannabis has still to overcome the political barrier which slows down its medical recognition.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".