Spatial-Temporal Quantitative Global Energy Differences between the Living and Dead Human Brain
Bibliographic record
Abstract
The dynamic differences between a living human brain and a clinically dead (fixed) human brain were measured over international Quantitative Electroencephalographic (QEEG) sites for 1 Hz increments between 1 Hz and 50 Hz. Although the expected greater power (μV2•Hz–1) for the living brain was apparent, the difference was particularly obvious for theta and low beta bands. The integrated square root values over the entire band indicated the difference in intrinsic charge-based energy between the living (higher) and dead brain was ~2•10–23 J. This quantity is remarkably proximal to the Cosmic Background Microwave value and would be consistent with the Hameroff-Penrose definition of consciousness that suggests a permeating presence derived from discrete physical events. A power value obtained by multiplying this increment of energy by the frequency of the universal hydrogen line resulted in ~10–12 W•m–2 when applied to the surface area of the human cerebrum. This value is the median flux density that has been measured from human brains during cognition and defines the ultra-weak photon emissions displayed by cells, tissue, and organisms. These results suggest that modern technology may now be sufficiently precise to discern the critical parameters that differentiate the living brain from the fixed “dead” brain. This information might be useful for future designs of virtual consciousness and simulations within cerebral space.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".