Bibliographic record
Abstract
Since time immemorial, people have attributed the causes of aftershocks, which bring numerous troubles to cities and settlements, to God's punishment for people's sins. The terrible earthquake of November 1, 1755 in Lisbon gave rise to a serious study of earthquake processes, and “thanks” to this catastrophe, geophysics took a huge step forward in the form of numerous scientific papers in the wake of this earthquake and the “cherry on the cake” in the form of the remarkable work of Mr. J. Michell (1760), where the source of the earthquake is not God Punishment, and a seismic wave! The second earthquake that had a significant impact on the development of geophysics was the earthquake in San Francisco on April 18, 1906. Unfortunately, the conclusions of the causes of this disaster, unlike the earthquake in Lisbon, had a negative impact on geophysics in the form of the adoption of Mr. Reid's theory of Elastic recoil, which led science into a dead end, from which geophysicists have not been able to find a way out for more than a hundred years. In this article, made in the style of a historical perspective on the development of geophysics, we will show the progress and regression of the Earth sciences over the past 300 years and reveal the real source of earthquake energy, which was pointed out by the genius W. Stukeley in the distant eighteenth century.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".