Cave fragmentation in a cave-to-mill context at the New Afton Mine part I: fragmentation and hang-up frequency prediction
Bibliographic record
Abstract
Block and panel caving methods are increasingly being proposed as an economical means for the excavation of ore deposits. The development of methods for predicting cave fragment size holds significant potential for reducing risk associated with cave mining projects. A fragmentation study was carried out for the New Afton B1 and B2 caves to generate fragmentation models that could be applied to future lifts. In part 1 of this paper, implications of fragmentation size for the mine are considered, whereas the effects on mill performance are addressed in part 2. Fragmentation measurements, from sieving and image-based methods, as well as historical logs of hang-up events are presented. Measurements showed that for the B1 and B2 caves, secondary fragmentation size, representing the size of material at drawpoints, is strongly related to faulting, height of draw and effects of the cave boundary.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".