High-Level Control in Lucid Dreams
Bibliographic record
Abstract
The objective of the present study is to explore lucid dream control strategies (LDCSs) facilitating the production of outcomes that are impossible in the real world. Participants are 107 adults who experienced at least one lucid dream per year. They completed an online survey including an open question on LDCSs. Responses were analyzed using a content analysis method with a consensus approach. The results revealed five categories of LDCSs used within the lucid dreams: verbal strategies, strategies based on the use of the dream’s objects or environment, strategies based on the use of the oneiric body, strategies based on the management of emotions, and other strategies. Within these categories, 35 LDCSs were identified. These were used individually or in combination. Three additional LDCSs were used in waking. In conclusion, several LDCSs that were identified could be tested in the context of the lucid dream therapy for chronic nightmares.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".