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Record W4250476137 · doi:10.21203/rs.3.rs-87807/v1

The Quantum Mechanism of Earthquakes as Exemplified by a Sudden Ejection of Rocks and Gas from a Rock Mass during the Process of a Coulomb Explosion

2020· preprint· en· W4250476137 on OpenAlexaff
Serguei Bychkov

Bibliographic record

VenueResearch Square · 2020
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicEarthquake Detection and Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGeophysicsCrustGeologyRock mass classificationVolcanic rockCoulombPhysicsEarth scienceVolcanoSeismologyQuantum mechanicsGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract At the moment, there are several hypotheses in geophysics that explain especially dangerous processes of the earth's crust movements - sudden outbursts of rocks and gas from a rock mass from the point of view of classical physics. Despite the fact that various macroscopic systems can be accurately described using classical mechanics and electrodynamics, a real mechanism and a working model of this phenomenon cannot be built. Consequently, to develop a model of sudden outbursts of rocks and gas, it is necessary to apply new approaches and methods, different from the description of macroscopic systems. This article describes a quantum version of the process of the ejection of rocks from a rock mass. In particular, we described the mechanism of the Coulomb explosion that occurs in the rocks of the earth's crust with a sharp change in rock pressure and built a model of the sudden release of rocks and gases. In our opinion, the quantum processes described by us can be sources not only of sudden outbursts and rockslide but also sources of more formidable phenomena - earthquakes and volcanic explosions.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.028
GPT teacher head0.299
Teacher spread0.271 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2020
Admission routes1
Has abstractyes

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