Assessment of Sortability Using a Dual-Energy X-ray Transmission System for Studied Sulphide Ore
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Bibliographic record
Abstract
In hard rock mining, sensor-based sorting can be applied as a pre-concentration method before the material enters the mill. X-ray transmission sensors have been explored in mining since 1972. Sorting ore of acceptable grade and waste material before processing at the mill can reduce the amount of tailings per unit of valuable metal in the mining operation and have many economic benefits. Ore samples used in this paper are from a polymetallic carbonate replacement deposit (gold-silver-lead-zinc sulphide) in Southeast Europe. This paper focuses on how the Dual-Energy X-ray Transmission (DE-XRT) data is generated and used for ore characterization and sortability for this sulphide ore. The method used in the DE-XRT analysis in this project is based on the dual-material decomposition method, which is used in the medical industry for radiology. This technique can distinguish sulphides from non-sulphides. However, the correlation developed between the DE-XRT response and the metal content is lacking. As a result, the DE-XRT response can only classify the material effectively but cannot reliably predict the metal content.
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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