Development of Patented Autonomous Quantum Gravitational Electric Energy Generator Prototypes
Bibliographic record
Abstract
After quantum physics modelling of Gravitational interaction from hypotheses, we performed experimental confirmation experiments of predicted increased Faraday’s induction. Brief and low energy electric discharges were made, at room temperature, into partially superconducting Graphite based devices, patented and named “emitters”, inserted in series with the primary low inductance of a transformer. The high voltage secondary inductance of that transformer was connected to a capacitor, so the secondary current oscillated during several milliseconds. We Measured the global energy efficiency of Faraday’s induction, during each electric discharge into the emitter of the primary circuit. We also measured evolution of the peak primary discharge current, and of its derivative, versus the initial charge voltage. We observed systematically a much larger than 100% energy efficiency. That energy efficiency increases with the primary discharge energy. The peak discharge current is observed to be much larger than predicted by Ohm’s Law, and the discharge current derivative is also observed to be much larger than classically predicted. Same experiments, performed with “normal conductive devices (control)”, gave energy efficiencies much lower than 100 %, independent of the stored energy. And their peak discharge currents and derivatives followed Ohm’s Law. From these confirmations of predicted results, we proposed and tested successfully concepts of Autonomous electric Generators prototypes, extracting their energy from the cosmological Gravitational quantum field. Their industrial use into electric vehicles should preserve Earth fossil energy resources, as well as reduce the detrimental climate effects of greenhouse gases emissions. Hypotheses are suggested to explain the observed experimental facts.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".