Bibliographic record
Abstract
The recent years have seen an unprecedented surge of psychedelic research. Studies with psilocybin (colloquially known as magic mushrooms), in particular, have shown promise in ameliorating symptoms of treatment-refractory depression, anxiety, and substance use disorder, among others 1 , 2 . Microdosing, the practice of regularly taking roughly a tenth of full psychedelic doses, is becoming increasingly popular 3 . These sub-perceptual doses cause no psychedelic effects, yet anecdotal reports suggest they carry substantial improvements to mental wellbeing. Popularized in-part by Silicon Valley developers and entrepreneurs, microdosing psilocybin and LSD is widely suggested to boost creativity, attention, sociability, while treating low mood and anxiety. Additionally, recent years have seen microdosing permeating the mainstream psychedelic scene. Several recent self-report survey studies demonstrate the overwhelming positive effects of microdosing on users’ mental health 3 , 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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.012 | 0.015 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".