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Record W2613995254 · doi:10.36487/acg_repo/711_27

In-Situ Dynamic Testing of Ground Support Using Simulated Rockbursts

2007· article· en· W2613995254 on OpenAlexfundno aff
Daniel Heal, Yves Potvin

Bibliographic record

VenueDeep mining · 2007
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
FundersAngloGold AshantiKalgoorlie Consolidated Gold MinesMinerals and Energy Research Institute of Western AustraliaNewcrest MiningBarrick Gold Corporation
KeywordsIn situComputer scienceGeologyChemistry

Abstract

fetched live from OpenAlex

The Australian Centre for Geomechanics (ACG) is conducting a number of simulated rockburst experiments in Western Australian underground mines as part of its Mine Seismicity and Rockburst Risk Management research project. By simulating rockburst damage using blasting, it is possible to gauge the performance of complete ground support systems (incorporating rockbolts or cables, surface support and the connections between them) in-situ when subjected to strong ground motion, as would be generated by a large seismic event nearby. This paper describes the testing method used and presents the results of simulated rockburst tests at a number of Western Australian mines on various ground support systems. A dynamic support classification is shown which compares the dynamic capacity of the ground support systems tested. The test results are compared to ground support performance observed in actual rockburst case studies.

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)0.002
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.026
GPT teacher head0.263
Teacher spread0.237 · 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

Citations20
Published2007
Admission routes1
Has abstractyes

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