Anomalous bodily-self experiences among recreational ketamine users
Bibliographic record
Abstract
INTRODUCTION: Out-of-body experiences present a unique paradigm to investigate cognitive and neural mechanisms of bodily-self processes and their disorders. Previous work on out-of-body experiences associated with sleep paralysis supported a model in which illusory movement experiences reflect disrupted bodily-self integration generating anomalous vestibular and motor sensations. Further disintegration and progression of the experience may then give rise to out-of-body feelings, which in turn may instigate out-of-body autoscopy. METHODS: The current study assesses the disintegration model through analyses of out-of-body experiences reports from an online survey of individuals reporting recreational ketamine use (n=128) and cross-validation in a sample of nonketamine polydrug users (n=64). Path analyses using intensity and frequency measures of anomalous experiences assess the fit of seven competing models. RESULTS: The disintegration model (illusory movement → out-of-body feelings → out-of-body autoscopy) emerged as the best fitting model overall and results support full mediation of the relation between illusory movement experiences and out-of-body autoscopy by out-of-body feelings. Moreover, lifetime measures of ketamine use predicted the frequency of illusory movement experiences. CONCLUSIONS: The results corroborate this structural model of out-of-body phenomena and encourage a framework for future studies into aetiological mechanisms of out-of-body experiences to include neurochemical systems.
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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 | 0.000 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".