Bibliographic record
Abstract
Cannabis is one of the most commonly abused drugs in the world and there is a widespread misconception that cannabis is a safe drug without adverse effects. Tetrahydrocannabinol (THC) is one of the main chemicals of cannabis and considerable research suggests that cannabis and THC may have severe consequences on mental as well as physical health. However, the cardiovascular effects of cannabis are not well known. This article outlines the first reported case of pediatric death due to myocarditis induced by cannabis exposure. The subject is an 11-month-old male without any previous medical history that presented to the emergency department with central nervous system depression. The patient then went into cardiac arrest and died. Autopsy revealed myocarditis as the cause of death. Post-mortem blood analysis further revealed high concentrations of Δ-9-THC which is a metabolite of THC that can be detected for 24 hours after exposure. Considering that no other alternate causes of myocarditis have been confirmed, this raises cannabis exposure as the most likely cause. Although this is the first case of death from cannabis-induced myocarditis, there have been other cases wherein which cannabis exposure lead to myocarditis in young males. Altogether, these cases highlight the need for further investigation into the cardiovascular effects of cannabis and to consider cannabis in the diagnosis of myocarditis.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| 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".