Assessing stope performance using georeferenced octrees and multivariate analysis
Bibliographic record
Abstract
This paper presents the first steps towards a new stope design approach, where stope overbreak (OB; rock mined outside of the design) and underbreak (UB; planned rock left behind) is assessed using statistical multivariate analysis (principal component analysis [PCA] and partial least square [PLS]) and georeferenced data measured at an approximately cubic metre resolution (octrees). Results showed that OB is observed in areas of the stope where there is a large blasting energy proxy, large undercut and towards the middle of the face. UB tends to be observed near the border of the faces and where there is large blasting standoff and toeing of the rings. The resolution of the data and the use of multivariate analysis have enabled the depiction of an accurate interpretation of the variation of stope performance along the design surface, going beyond the simple per face analysis.
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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 | 0.001 | 0.002 |
| 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 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".