EXPERIMENTAL FACILITATION OF THE SENSED PRESENCE IS PREDICTED BY THE SPECIFIC PATTERNS OF THE APPLIED MAGNETIC FIELDS, NOT BY SUGGESTIBILITY: RE-ANALYSES OF 19 EXPERIMENTS
Bibliographic record
Abstract
If all experiences are generated by brain activity, then experiences of God and spirits should also be produced by the appropriate cerebral stimulation. During the last 15 years experiments have shown that the sensed presence of a "Sentient Being" can be reliably evoked by very specific temporal patterns of weak (<1 microT) transcerebral magnetic fields applied across the temporoparietal region of the two hemispheres. Recently Granqvist et al. (2005) attributed these effects to suggestibility and exotic beliefs. Re-analyses with additional data for 407 subjects (19 experiments) showed that the magnetic configurations, not the subjects' exotic beliefs or suggestibility, were responsible for the experimental facilitation of sensing a presence. On the other hand, the subjects' histories of sensed presences before exposure to the experimental setting were moderately correlated with exotic beliefs and temporal lobe sensitivity. Several recent experiments have shown that the side attributed to the presence at the time of the experience is sensitive to the temporal parameters of the fields, the hemisphere to which they are maximized, and the person's a priori beliefs. The importance of verifying the specific timing and temporal pattern of the software-generated fields and following an effective protocol is emphasized.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".