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Record W2690238944 · doi:10.1016/j.proeng.2017.05.246

Assessment of Rockburst Hazard Based on the Data of Mine Seismology

2017· article· en· W2690238944 on OpenAlexaff
В. Н. Опарин, V. A. Vostrikov, O. A. Usoltseva, S. N. Mulev, E. Rodionova

Bibliographic record

VenueProcedia Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsNickel Institute
Fundersnot available
KeywordsInduced seismicityGeologySeismic hazardSeismologySeismic energyRock mass classificationMining engineeringPassive seismicHazardGeotechnical engineering

Abstract

fetched live from OpenAlex

Processing and interpretation of huge array of mine seismicity data obtained in mines of Norilsk Nickel Mining and Metallurgical Company has revealed the “pulsating” mode of seismic energy release on the background of an increase in the strata pressure and, based on the information on monthly migration of reduced centers of seismic energy release within the mine fields, enabled development of a rockburst hazard criterion for individual rock mass areas. The prognostic criterion of the limiting state of a rock mass area is developed based on the ratio of kinematic characteristics of seismic events, which are the velocity of a reduced center of seismic energy release and the apparent velocity of “migration” of individual seismic events closely timed within the ranges of stress concentration zones inside the mine fields. Verification of this criterion using an ample seismic data base accumulated for a number of years in a mine of Norilsk Nickel has displayed high sensitivity of the criterion towards the change in the stress state of rock mass areas under monitoring.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.253
Teacher spread0.225 · 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 designObservational
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
Published2017
Admission routes1
Has abstractyes

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