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Hallucinogens in Mental Health: Preclinical and Clinical Studies on LSD, Psilocybin, MDMA, and Ketamine

2020· review· en· W3109908198 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Neuroscience · 2020
Typereview
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsCarleton UniversityMcGill University
FundersNational Institute of Mental HealthInstitute of Neurosciences, Mental Health and AddictionFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchGovernment of Canada
KeywordsPsilocybinHallucinogenMDMAMescalinePsychologyKetaminePharmacologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

A revamped interest in the study of hallucinogens has recently emerged, especially with regard to their potential application in the treatment of psychiatric disorders. In the last decade, a plethora of preclinical and clinical studies have confirmed the efficacy of ketamine in the treatment of depression. More recently, emerging evidence has pointed out the potential therapeutic properties of psilocybin and LSD, as well as their ability to modulate functional brain connectivity. Moreover, MDMA, a compound belonging to the family of entactogens, has been demonstrated to be useful to treat post-traumatic stress disorders. In this review, the pharmacology of hallucinogenic compounds is summarized by underscoring the differences between psychedelic and nonpsychedelic hallucinogens as well as entactogens, and their behavioral effects in both animals and humans are described. Together, these data substantiate the potentials of these compounds in treating mental diseases.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.988
Threshold uncertainty score0.971

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.471
GPT teacher head0.584
Teacher spread0.112 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it