DISCUSSION ON THREE CHARACTERISTIC FOCAL DEPTHS OF MINING-INDUCED SEISMICITY
Bibliographic record
Abstract
In the current study,three characteristic focal depths of mining-induced seismicity in coalmines,i.e. initiation depth,roof upper-bound depth,and floor lower-bound influence depth,are identified from field microseismic monitoring data. These characteristic depths depend on the relative distance between the hypocenter of a seismic event and ground surface or the location of the roof and floor of the coal seam. The initiation depth is the one beyond which rockbursts will happen. The roof upper-bound depth is defined as the depth of the seismic events located above the roof whose magnitudes are greater than certain thresholds;and the floor lower-bound influence depth is defined as the difference between the depth of the observed maximum seismic event below the floor and the depth of the floor. The mechanisms of the characteristic focal depths are also discussed. The initiation depth is explained by a power law model considering coal strength and the stress acting on the coal body,the roof upper-bound depth is explained by a bending model of a thick plate or beam;and the floor lower-bound influence depth is explained by the combined effect of elastic rebound due to unloading and the effect of Poisson′s ratio as well as the influence of active faults. Finally,the impact of understanding the characteristic focal depths on mining safety is discussed. It is expected that a better understanding of these characteristic depths will facilitate the mitigation and control of mining-induced seismic hazards in underground coalmines.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".