Growing up high: Understanding the impacts of adolescent cannabis use on mental health and brain Development
Bibliographic record
Abstract
Adolescence represents one of the most crucial periods of human brain development. This unique neurodevelopmental window involves a complex interplay of synaptic re-modelling, the establishing of cortical and sub-cortical emotional processing and cognitive neural circuits along with a greater propensity for engaging in risky behaviours and experimentation with illicit drugs. A growing body of both clinical and pre-clinical evidence has demonstrated that exposure to cannabis, and more specifically, Δ-9-tetrahydrocannabinol (THC), the primary psychoactive compound in cannabis, can strongly increase the likelihood of developing serious neuropsychiatric disorders in later life. Adolescent THC exposure is linked to long-term cognitive impairments, emotional dysregulation, mood disorders and increased vulnerability to schizophrenia. The interplay between adolescent THC exposure and mental health risks have been linked to a wide array of underlying neurobiological pathologies, including structural and morphological alterations in brain circuits linked to cognitive function and emotional regulation. Despite this growing body of data, there remains considerable confusion and misinformation regarding how and why adolescent cannabis use can ultimately increase these psychopathological risk factors. Nevertheless, the confluence of clinical and pre-clinical neuroscience research related to these questions is finally providing much needed insight into the relative risks and identifying useful biomarkers that may ultimately allow us to establish more reliable criteria and guidelines for safer cannabis access and help mitigate these risks to mental health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".