Seismic methods in mineral exploration and mine planning: A general overview of past and present case histories and a look into the future
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT Due to high metal prices and increased difficulties in finding shallower deposits, the exploration for and exploitation of mineral resources is expected to move to greater depths. Consequently, seismic methods will become a more important tool to help unravel structures hosting mineral deposits at great depth for mine planning and exploration. These methods also can be used with varying degrees of success to directly target mineral deposits at depth. We review important contributions that have been made in developing these techniques for the mining industry with focus on four main regions: Australia, Europe, Canada, and South Africa. A wide range of case studies are covered, including some that are published in the special issue accompanying this article, from surface to borehole seismic methods, as well as petrophysical data and seismic modeling of mineral deposits. At present, high-resolution 2D surveys mostly are performed in mining areas, but there is a general increasing trend in the use of 3D seismic methods, especially in mature mining camps.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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