Variable Viscosity of Water as the Controlling Factor in Energetic Quantities that Control Living Systems: Physicochemical and Astronomical Interactions
Bibliographic record
Abstract
The emergence of energy from the product of viscosity, volume and intrinsic or extrinsic frequency indicates that the ten fold difference in this property displayed by water could define the boundary of the physicochemical conditions of living systems. Intra-aqueous energy induced by geomagnetic variations and experimental time-varying magnetic fields within specific volumes of water maintained in static, dark conditions can be manifested as photon emissions with shifts in spectral power that approximate the width of the plasma cell membrane. Various manipulations of the viscosity of water accurately predicted the frequency required to affect intracellular organelles such as vesicles as well as the intramolecular pressures that affect interactions with photons. Application of the Smoluschowski-Einstein relation to the proton, the mediator of pH and the dynamics of the hydronium ion, potentially explained the vector characteristics of the frequency band of extremely low frequency magnetic fields that slow malignant cells. The derivation of viscosity from the inverse of the Newtonian Gravitational Constant, diffusivity and the square of the applied frequency indicates that resonant oscillations between the solid earth and the atmosphere and unit variations in solar flux density may be relevant variables.
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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".