The Secret of the Titius-Bode Law: A New Theory on How Our Planetary System Came Into Existence
Bibliographic record
Abstract
Our planetary system still has several unsolved riddles. One of them is the Titius-Bode law. With the aid of this law, it is easy to find the distances of planets from the sun. For many astronomers, this is coincidence. They argue that there is no known physical mechanism that generates a particular sequence of planets’ distances. However, if one investigates the structure of the law, it quickly becomes clear that the Titius-Bode law is directly connected with the formation of planets. Our planets did not come into existence through so-called accretion. At the beginning of its existence, the sun was presumably a T-Tauri star. These are young stars in the process of their formation. They pulsate irregularly, thereby accelerating clouds of plasma in the surrounding dust disk. Each of these eruptions thus generated a planet. This of course goes much more quickly than if they had to be formed from the dust of planetary disks. This new theory not only describes how the planets and the distances of the planets came into existence. It also gives a new description of how the moon came into existence, the cause for large moon craters, the slow rotation of Venus, the formation of the asteroid belt, the high iron content of the planet Mercury, and the sun’s loss of rotational impulse, among other things.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.030 |
| Scholarly communication | 0.007 | 0.029 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.005 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".