Article Demonstration of Excess Correlation in Non-Local Random Number Generators Sharing Circular, Changing Angular Velocity Magnetic Fields
Bibliographic record
Abstract
To test if temporally-coupled diametric shifts in parity could be demonstrated for non-local distances between “random” events generated by electron tunnelling-based circuits, two REG (Random Event Generators) were each exposed within a circular array of solenoids separated by 10 m. Each circular array generated a patterned rotating magnetic field that has previously produced transient excess correlation and entanglement in photon reactions and alterations in pH in spring water. During a 30 min interval the REGs were exposed first to an accelerating group velocity embedded with a diminishing frequency/phase-modulated field (the primer) followed by a decelerating group velocity embedded with an increasing frequency/phase-modulated magnetic field (the effector). Only after exposures for about 4 min to the second (effector) condition that is known to manifest the effects of entanglement did the random numbers deviate significantly and by more than one standard deviation in an opposite direction to each other. The estimated increments of energy were between 10 -21 and 10 -20 J which is within the range of the energy derived from the universe’s total force per Planck’s voxel distributed over the distance of the hydrogen wavelength. These results indicate that excess correlation can be generated within “random”, quantum electronic processes whose spatial domains are similar to neuronal synapses at the macro-level by appropriate applications of weak, microTesla level, magnetic fields.
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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 | 0.001 |
| 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) | 0.001 | 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".