Low-magnitude seismicity monitoring in rocks
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The authors calculate possible errors in characterization of low-magnitude seismicity sources using the Brune model and methods of identification of seismic event energy class and local magnitude. The adequacy of the model has been proved by comparing its results with the recordings of seismic vibrations in the North Ural Bauxite Mine. The errors due to the drastic distortion of the emission spectrum become significant at the distance of 1000 m from the emission source and grow as the distance increases. Cases of great deviations from the similarity law are analyzed based on the actual seismic monitoring in the North Ural Bauxite Mine, in mines in Poland, Finland and Canada, as well as in water basins. It is shown that phenomena due to physical difference of various size fracturing dynamics do not radically change a seismic source capacity. Other causes, due to instrumentation shortcomings or incorrect data interpretation, may result in overestimated seismic energy and scaling-up of low-magnitude seismic events.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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 it