Safe blasting near rock glaciers
Bibliographic record
Abstract
Large mining projects have been developed and operated in glacial and periglacial environments around the world for decades.This leads to the inevitable fact that certain mining operations are located in close proximity to glacial and/or periglacial cryoforms such as glaciers or rock glaciers, respectively.In response to an increase in public awareness of these projects and climate change, regulatory bodies in various jurisdictions have heightened their focus on potential anthropogenic impacts to these cryoforms.Mining-induced blasting in close proximity to these cryoforms is considered to potentially impact these landforms.It therefore becomes of operational, regulatory and environmental importance to be able to design blasting patterns that do not cause any impact on these geological features for mining operations near such cryoforms.A critical component when designing production blasts in such settings is to determine the so-called Charge Weight per Delay Interval (CWPDI) of an acceptable blast.This paper outlines a simplified method for determining the maximum acceptable CWPDI for blasting as a function of the distance to the selected cryoform.The procedure requires knowledge of the type and weight of explosive per blast hole, the time delay pattern, in situ Peak Particle Velocity (PPV) and frequency measurements at varying distances from the blast, and a basic understanding of the cryoform's geometry and strength properties.Recognizing that not all projects will have access to such extensive data, some parameters and simplified equations are suggested to guide the assessment in those situations.This work serves to highlight the significance of responsible, informed mining practices within a vulnerable environment.1
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".