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Record W4362524302 · doi:10.24425/ams.2021.138598

Application Cumulative Tensile Explosions for Roof Cutting in Chinese Underground Coal Mines

2023· article· en· W4362524302 on OpenAlexaff
Jun Yang, Wenhu Bian, Kuikui Chen, Hongyu Wang, Chen Cao

Bibliographic record

VenueArchives of Mining Sciences · 2023
Typearticle
Languageen
FieldEngineering
TopicStructural Response to Dynamic Loads
Canadian institutionsGeomechanica (Canada)
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsRoofCoal miningMining engineeringMine safetyForensic engineeringUltimate tensile strengthIndustrial chemistryGeologyEngineeringGeotechnical engineeringCoalStructural engineeringMaterials scienceMetallurgyWaste management

Abstract

fetched live from OpenAlex

Cumulative blasts are an important controlled blasting method used to control the propagation of cracks in the predetermined direction. however, traditional cumulative blasts are associated with long processing times and poor blasting effects. A simple blasting technology called bilateral cumulative tensile explosion (BCTE) is proposed in this paper. There are two application types where BCTE is used. The first application is used to control the stability of high-stress roadways in both Wangzhuang mine 6208 tailgate and hongqinghe mine 3-1103 tailgate. The second application is used to replace the backfill body in gob--side entry retaining (gER) in Chengjiao mine 21404 panel, Jinfeng mine 011810 panel and Zhongxing mine 1200 panel. The first application type reveals that BCTE can significantly reduce the deformation of the surrounding rock and reduce the associated maintenance cost of the roadways. Whereas the second application type, the roadway deformations are smaller, the process is simpler, and the production costs are lower, which further promotes gER and is of significance towards conserving resources.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.026
GPT teacher head0.306
Teacher spread0.280 · 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 designBench or experimental
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

Citations8
Published2023
Admission routes1
Has abstractyes

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