Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Psilocybin is a naturally occurring psychoactive compound, which has been used for ages in traditional settings for religious and therapeutic use. Recent studies have renewed interest in psilocybin for its potential therapeutic benefits in treating depression and anxiety. The pharmacodynamics of psilocybin are complex, involving its rapid conversion to psilocin and its activity on various serotonin receptors, particularly the 5HT2A/C and 5HT1A receptors. In addition, psilocybin can increase glutamate release, which is believed to be an important mechanism underlying its therapeutic effects. Clinical trials have demonstrated that psilocybin has a long-lasting antidepressant effect, with little to no side effects. However, it is necessary to further study the mechanisms underlying its therapeutic potential and to optimize its use in clinical settings. Overall, the promising findings suggest that psilocybin may offer a valuable alternative to traditional antidepressant therapies for individuals suffering from depression and anxiety. Meanwhile, studies have shown that this drug also has certain benefits for mental disorders such as addiction and obsessive-compulsive disorder. Thus, it is necessary to continue exploring the potential of psilocybin as a novel strategy in treating mental health disorders.
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.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it