Psychophysical interactions with a double-slit interference pattern: Exploratory evidence of a causal influence
Bibliographic record
Abstract
An experiment we conducted from 2012 to 2013, which had not been previously reported, was designed to explore possible psychophysical effects resulting from the interaction of a human mind with a quantum system. Participants focused their attention toward or away from the slits in a double-slit optical system to see if the interference pattern would be affected. Data were collected from 25 people in individual half-hour sessions; each person repeated the test ten times for a total of 250 planned sessions. “Sham” sessions designed to mimic the experimental sessions without observers present were run immediately before and after as controls. Based on the planned analysis, no evidence for a psychophysical effect was found. Because this experiment differed in two essential ways from similar, previously reported double-slit experiments, two exploratory analyses were developed, one based on a simple spectral analysis of the interference pattern and the other based on fringe visibility. For the experimental data, the outcome supported a pattern of results predicted by a causal psychophysical effect, with the spectral metric resulting in a 3.4 sigma effect (p = 0.0003), and the fringe visibility metric resulting in 7 of 22 fringes tested above 2.3 sigma after adjustment for type I error inflation, with one of those fringes at 4.3 sigma above chance (p = 0.00001). The same analyses applied to the sham data showed uniformly null outcomes. Other analyses exploring the potential that these results were due to mundane artifacts, such as fluctuations in temperature or vibration, showed no evidence of such influences. Future studies using the same protocols and analytical methods will be required to determine if these exploratory results are idiosyncratic or reflect a genuine psychophysical influence.
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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 | 0.003 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".