Convergence of Numbers of Synapses and Quantum Foci within Human Brain Space: Quantitative Implications of the Photon as the Source of Cognition
Bibliographic record
Abstract
Quantitative solutions involving classical methods indicated that the numbers of quantum foci within the human cerebrum are the same order of magnitude as the numbers of synapses in the cerebral cortices. The Bohr frequency for the magnitude of the quantum associated with the removal of one nucleus from another is within the range of the width of synapse (~1 µm) while the recoil energy from a rest mass photon is equivalent to the energy produced by the entire field of dynamic neurons per second. The intrinsic energy (10-20 J) associated with each action potential is similar to the gravitational potential energy from Planck’s mass applied across 1 µm. Both the endogenous cerebral magnetic field strength which is similar in magnitude to intergalactic intensities and the interaction between weak geomagnetic variations and the cerebrum’s electric dipole current are associated with photon flux densities in the order (10-11 W∙m-2) that have been measured in the laboratory. The perspective of the human cerebral volume as a field of foci of photon quanta offers different perspectives for the intrinsic nature of consciousness and cognition and their influence by phenomena from astronomical origins.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".