Microseismic Monitoring of Tailings Dams - Evaluation of Seismic and Noise Sources
Bibliographic record
Abstract
The dataset originates from the manuscript titled "Microseismic Monitoring of Tailings Dams - Evaluation of Seismic and Noise Sources," currently under submission to Brazilian Journal of Geophysics. The database is organized into four distinct categories, each serving a specific purpose: Signal: This category comprises common signals, which are likely to be observed at various stations worldwide. It includes data from both blast events and natural seismic occurrences; Site-specific Signal: These signals are unique to the specific location or a single station. They primarily consist of data obtained from pulse tests conducted at the site; Noise: Within this category, common noise sources are documented, which are also anticipated to be observed at other stations globally. The noise sources encompass mechanical disturbances such as those from backhoes, drills, excavators, and trucks. Additionally, data related to natural phenomena such as lightning, thunder, and combinations thereof (lightning accompanied by thunder) are also cataloged here; Site-specific Noise: This category comprises noise sources that are specific to the particular location or a single station. The primary source identified here is digitizer interference.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.025 |
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".