Antigravity, an Answer to Nature’s Phenomena including the Expansion of the Universe
Bibliographic record
Abstract
The gravitational attraction force being proportional to the mass has been experimentally shown for several hundred years now, but no gravitational repulsion has been identified within the accepted scientific reasoning. Here, we show that the gravitational repulsion force, similar to the gravitational attraction among particles has also been in existence in nature but, yet to be recognized. The results of experiments are shown in detail and are discussed in the recent series of-publications. It is also shown here that this gravitational repulsion force is proportional to the temperature which is an indicator of thermal energy of the particle, similar to the gravitational attraction that is proportional to the mass of the particle. The situations where heavy particles such as iodine, tungsten, and thorium in vacuum move against gravitational force have already been shown qualitatively. The increase in time-of-fall of water droplets (slowing down of fall) with rise in temperature is also quantitatively discussed. This article discusses two major phenomena observable in nature, clouds and the expansion of universe, which could be more preciously explained by the concept of antigravity.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".