Spectral Power Densities of the Fundamental Schumann Resonance Are Enhanced in Microtubule Preparations Exposed to Temporally Patterned Weak Magnetic Fields: Implications for Entanglement
Bibliographic record
Abstract
Preparations of microtubules (MT) from mouse melanoma cells emitted predictable photon counts when sampled 50 times per s (every 20 ms) that depended upon the numbers of these preparations. Counterbalanced serial 4 min exposures of the same MT to different temporally patterned magnetic fields with intensities between 3 and 10 μT did not alter the absolute photon emissions but shifted their spectral power densities (SPD). Compared to baseline (no field) 4 min periods there were conspicuous increases of power within the 7.7 to 7.8 Hz band during the 4 min exposures to patterned magnetic fields that facilitate long-term potentiation in neurons but not during exposures to a pattern associated with analgesia. A priori predictions of the shift in frequency (Δf) based upon the median mass of tubulin dimers, known numbers of unit charges per dimer, and the strength of the applied fields predicted a range between 0.11 and 0.14 Hz. SPD demonstrated two peaks at 7.74 Hz and 7.87 Hz or a Δf=0.13 Hz. The results indicate only 4 min exposures of microtubule preparations to specifically physiologically patterned magnetic fields associated with memory consolidation enhance the power of the numbers of photon emissions in a frequency band that is very similar to the fundamental Schumann Resonance.
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 | 0.000 | 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".