Bibliographic record
Abstract
Cannabis TherapyThe authors addressed a topic of increasing relevance.In this context we wish to mention a treatment option for posttraumatic stress disorder (PTSD) that is mostly not known in Germany: (self) medication with cannabis products.In North America, countries in the Balkans, and countries in the Middle East, this form of treatment is widespread.In Rhode Island (US), some 40% of all 4300 state-registered patients consuming cannabis were recommended cannabis treatment for PTSD by their doctors.The supreme court of law in Croatia decided in 2009 that war veterans were legally allowed to use cannabis.According to an observational study from Israel that was presented in 2011, cannabis has a relevant therapeutic benefit in the treatment of PTSD.In a clinical study from Canada, the cannabinoid nabilone reduced nightmares and flashbacks (1).A case report from Germany (2) describes a patient in whom severe uncontrolled flashbacks, panic attacks, and selfharm owing to severe PTSD notably improved as a result of self-treatment with cannabis products.We can assume that very few patients with PTSD actually report their self-medication to their treating physicians.According to animal studies, the therapeutic effect of cannabinoids can be explained by the fact that the amygdala, which is responsible for storing memories and fear, is under the control of the endogenous cannabinoid system.Flooding the amygdala with endocannabinoids therefore results in the elimination of disagreeable memories (3).In a controlled clinical study of extinction learning, the active substance in cannabis, tetrahydrocannabinol (THC), prevents the reappearance of fear, so that modulators of the cannabinoid system have been suggested for the treatment of anxiety disorders (4).
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.044 | 0.038 |
| Insufficient payload (model declined to judge) | 0.016 | 0.010 |
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".