An Assessment of Unpredictability in the Design of Hydraulic Fracturing for Stress Amelioration Around Underground Excavations
Bibliographic record
Abstract
In underground mining operations, stress-induced hazards such as rock bursts are more likely to occur as mining continues. In cave mining operations, stress concentrations can form around underground openings due to the redistribution of the in situ stress.Destress blasting is a common method for reducing rockbursts. Recently, hydraulic fracturing has been investigated as an alternative method for stress amelioration in underground mines, for it may provide more control of fracture geometry than blasting; however, the unpredictability in the HF governing parameters must be properly characterized and incorporated into the design and analysis of fracture arrays. Typically, in the early stages of design, parameter uncertainty is generally epistemic, and the appropriate uncertainty model should be applied. The use of deterministic estimates neglects any parameter uncertainty. It is only when additional data are obtained and the parameters are characterized more precisely that more complex methods of analysis can be applied.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".