Bibliographic record
Abstract
Currently,the different methods for classification of mining-induced seismicity have no relation with each other.In order to be convenient for prediction,prevention and control of the mining-induced seismicity,based on the latest research results on the mechanism of the disasters,the classification of mining-induced seismicity is presented in this paper,following the principles of benefiting disaster prevention and control and non-conflicting to practices adopted both at home and abroad.The concept,principle and advantages of the hiberarchy classification of the mining-induced seismicity are given.5 classes and 16 types of mining-induced seismic events are classified based on the influence of in-situ tectonic stress field,physical and mechanical properties of rocks,rock mass structures,correlation between seismicity and mining activity,source of mining-induced stress change,and the locations of seismic sources and rock mass failure.The importance of regional tectonic stress field and stress change due to mining is emphasized in the mining-induced seismicity classification,research,and control.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".