Bibliographic record
Abstract
In a suburb of Vancouver, Canada, a nondescript three-story building sits alongside a strip of parking lots. From the outside, it looks like an ordinary commercial office space. But inside is something more extraordinary: rows of shelves stacked with plastic tubs full of magic mushrooms—mushrooms that contain the hallucinogenic chemical psilocybin. In a year, enough psychedelic mushrooms can be produced here to send 80,000 people on hallucinogenic trips.Psilocybin is a regulated, illicit substance in most countries, including Canada. But in this facility, run by Filament Health, the mushrooms are not grown for the black market; they are destined for research and clinical trials. These mushrooms could help determine if something important has been missing from psychedelics research.Psilocybin is a psychedelic compound that, once broken down by the body into psilocin, activates receptors in the brain to unleash a mind-altering experience. After decades of stigmatization, research on psychedelics is finally having a heyday. The research on psilocybin is unveiling its potential to treat challenging mental health conditions like depression, obsessive compulsive disorder (OCD), and stimulant- and opioid-use disorders.To date, most scientific research on psilocybin has been done with synthetic versions of the compound, not psilocybin from magic mushrooms themselves. Psilocybin was first synthesized in 1958 and synthetic psilocybin has remained the gold standard for testing due to its consistency and cheap production. But a small group of scientists posit that the magic of these mushrooms is more than their psilocybin alone. Over a dozen different compounds have been identified in magic
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.002 |
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 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".