Stepped frequency GPR field trials in potash mines
Bibliographic record
Abstract
Separations, which form along stratigraphic clay seams in the roofs of potash mines, pose a serious safety concern. If these separations go undetected they can lead to falls of ground. The current method of identifying the location and extent of these separations is through manual scaling (sounding) using an aluminium rod. The potash mining companies would likte to have a tool, which could quickly and reliably detect these separations and distinguish between separations and clay seams. This paper presents the results of field trials undertaken at various potash mines in SaskatchewanICanada belonging to the member companies of the Saskatchewan Potash Producers Associations. The radar device used for these field trials was RST?s SUSI (Multi Purpose Sub Surface Imager) radar system, which has the ability of working over various bandwidths. Four mines were chosen for these field trials, covering the different geological characteristics encountered in the Saskatchewan potash mines. These field trials indicated that stepped frequency ground penetrating radar technology could be ?tuned? to identify both separations and clay stratigraphy in the softrock, potash mine environment, based on the different spectral responses of the features.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".