Bibliographic record
Abstract
Strainburst is the most frequently encountered type of rockburst in underground mines. Strainburst occurs when the stress near the excavation boundary reaches the peak strength of the rock mass causing it to fail suddenly and violently. To mitigate strainburst damage risk, effective rock support is needed. In strainburst-prone grounds, it is critical to have rock support components to fulfill the role of rock reinforcement first to prevent rock failure. On the other hand, well-retained and reinforced rock masses may be excessively deformed and fail violently. In such a case, yielding elements are needed in the rock support system to absorb the excess strain energy released due to rock failure. The conventional method to support strainburst-prone grounds is to install rock reinforcement system using rebar and mesh first and then install yielding support system using dynamic rockbolts at a later stage. This two-stage rock support installation process is not effective because it can adversely impact mine production schedule. This paper presents a new, patented dynamic rockbolt, which is called superbolt and is developed for rock support in burst-prone grounds. Laboratory testing confirmed that the superbolt has superb capacity to achieve the goal of reinforcing and holding rock masses. The superbolt is characterized by high dynamic energy absorption capacity, consistent performance, and the ability to withstand repeated dynamic loading. The new rockbolt can be used in a one-pass rock support system to facilitate rapid drift development in underground mines and increase mine safety and productivity.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".