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Record W2896023031

Multivariate statistical analysis to investigate the seismic response to production blasting at Goldcorp Eleonore

2018· article· en· W2896023031 on OpenAlexaff
Jocelyn Tuleau, Martin Grenon, Carl Duchesne, Kyle Woodward, Pierre-Luc Lajoie

Bibliographic record

VenueUWA Profiles and Research Repository (University of Western Australia) · 2018
Typearticle
Languageen
FieldEngineering
TopicMineral Processing and Grinding
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMultivariate statisticsRock blastingMultivariate analysisStatistical analysisProduction (economics)GeologyStatisticsMathematicsGeotechnical engineeringEconomics
DOInot available

Abstract

fetched live from OpenAlex

The blasting of mining stopes is an important driver for mine seismicity. The factors controlling seismic response are not well understood. Mines mostly rely on the number of events and associated moment magnitudes. Geological and operational parameters are often neglected although known to be potential seismic drivers. A database was created for more than 83 production blasts between 230 m and 800 m below the surface from March 2016 to June 2017 at the Goldcorp Eleonore mine. The database consists of 78 parameters defining spatial, temporal, mining, geometrical, geological, drill-and-blast, and temporal blast properties and their associated seismic response. A multivariate statistical analysis was conducted using the created database to better understand the key factors controlling the seismic response of the rock mass to production blasting. The geological structures’ orientation and location relative to the stope, the stope geometry and the drilling pattern were identified as major factors contributing to induced seismicity at the Eleonore mine.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.715
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

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

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 head0.064
GPT teacher head0.314
Teacher spread0.250 · 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 teacher head, 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

Citations0
Published2018
Admission routes1
Has abstractyes

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