Multivariate statistical analysis to investigate the seismic response to production blasting at Goldcorp Eleonore
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".