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Record W4406667242 · doi:10.1556/2054.2024.00431

Experiential dimension of psilocybin-assisted therapy training: Necessity or hindrance to wider accessibility?

2025· article· en· W4406667242 on OpenAlexaff
Louis Plourde, Sue-Ling Chang, Houman Farzin, Jean-François Stephan, Jean‐Sébastien Fallu, Michel Dorval

Bibliographic record

VenueJournal of Psychedelic Studies · 2025
Typearticle
Languageen
FieldPsychology
TopicPsychedelics and Drug Studies
Canadian institutionsCentre intégré de santé et de services sociaux de Chaudière-AppalachesJewish General HospitalUniversité de MontréalMcGill University Health CentreUniversité Laval
Fundersnot available
KeywordsPsilocybinExperiential learningDimension (graph theory)PsychotherapistPsychologyTraining (meteorology)HallucinogenPsychiatryPedagogyMathematics

Abstract

fetched live from OpenAlex

Abstract The discussion surrounding the necessity of acquiring personal experience of non-ordinary states of consciousness in the course of psilocybin-assisted therapy training is crucial, as it can affect treatment safety, effectiveness and accessibility. As such, the ethical and practical issues associated with such a training standard require timely consideration in jurisdictions where this intervention is endorsed and integrated into healthcare. We believe the most balanced and ethical approach is to make psilocybin legally available for professional training without making it a requirement.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.007
Scholarly communication0.0030.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.000

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 head0.204
GPT teacher head0.493
Teacher spread0.288 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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