Article Potential Experimental Demonstration of the Entanglement Velocity of 10 23 m·s -1 during Trans-Atlantic Excess Correlation of Paired Brain Activity
Bibliographic record
Abstract
Two separate approaches have suggested that the diffusivity parameter or diffusion velocity of ~10 23 m·s -1 may be the quantitative value for the latency for displays of excess correlation or the consequences of entanglement. We have shown that pairs of individuals separated by 6,000 km but sharing toroidal magnetic fields with changing angular velocities displayed clear excess correlations in specific theta and gamma frequency power values over the right caudal hemispheres. The effect occurred only during the component of the exposure that has revealed excess correlations in photon and pH reactions separated by non-local distances. The predicted latency for the entanglement effects over distances of 6,000 km would be ~10 -17 s while the time required for 1 orbit of an electron is ~10 -16 s. Specific values indicated that between 10 and 30 s would be required before the entanglement would emerge within the domain of electronic matter. Quantitative measurements of the indicator of excess correlation in brain activity during the optimal interval of magnetic field configuration indicated the emergence occurred between 20 and 30 s after the effector field (but not the primer field) had been activated around the cerebrums of both subjects. The effect was clear for all 5 pairs of subjects. The results suggest but do not prove that the latency for entanglement may display a real time value coupled to the velocity of a diffusivity term derived from the relationship between four-dimensional geometry and the weighted products of Gravity and the mass, width and duration of the universe.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".