Network modelling of underground mine layout: two case studies
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The dominant working structure of an underground mine is a set of interconnected tunnels which provides access to ore zones and haulage of ore from the designated ore zones to the mill. This set of interconnected tunnels forms a network. We describe a mathematical network model and the modelling features of our two software tools for designing underground mine layouts that minimise associated costs. The application of these techniques is illustrated in two industry case studies. In the first, we apply the underground network optimisation tool to design an extension to an Australian gold mine where 15 new distinct orebodies are located in a 3 km long region, several hundred metres underground. In a second case study, we design a single decline for accessing a large orebody where a turning circle constraint is a significant factor. An efficient decline is found using the decline optimisation tool.
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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 | 0.002 | 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