Bibliographic record
Abstract
Applying analysis techniques developed for naturally occurring earthquakes to mine seismicity is common practice; however, these methodologies rarely consider the influence of blasting on the dynamic rock mass failure processes observed in mines. Due to the complex nature of bulk orebody extraction at depth, quantifying discrete seismic responses to mining can be challenging. This paper identifies seismic responses to mining by pairing single-link clustering with finite temporal windows bound by mine blasting practices. A methodology is presented to quantify the space−time characteristics of these responses using four seismic response parameters (SRPs): distance to blast, distance to centroid, time after blast, and time between events. Using SRPs, seismic responses to mining can be quantitatively classified as induced, complex, or triggered (with respect to discrete mine blasting). Because these response parameters do not require an extensive and (or) triaxial dense sensor array, they are applicable to a variety of underground mining operations. In this work, SRPs are applied to 189 discrete seismic responses occurring over 2 months of active mining, and a 2 week shutdown period, at Agnico Eagle’s LaRonde 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".