Deviation to mucking analysis
Bibliographic record
Abstract
Deviations in drill holes during underground mining substantially impact operating efficiency and safety. An examination of six stopes at Thompson Mine revealed systematic deviations of roughly 1 m (3 ft) from the designated drill hole configuration. Excessive deviations may result in imprecise ore body targeting, elevated operational expenses, and possible safety risks. A correlation was identified between the percentage of holes deviating beyond the average and the mucking rate, indicating that to sustain an average of 544 tonnes (600 tons) per day, less than 21% of holes should surpass the average deviation. It is also essential that drill speeds average 9.14 m (30 ft) per hour, particularly for novice operators, to reduce hole deviation. Regulated drilling rates improve precision, resulting in more efficient and economical operations. Decreased drilling rates mitigate the likelihood of misalignment and structural complications. Efficient management of drill hole variations necessitates sophisticated drilling tools, meticulous planning, and ongoing monitoring to guarantee adherence to the designated drill trajectory. Mining operations can achieve improved resource recovery, decrease waste, and enhance production by limiting deviations. Mitigating drill hole deviations is crucial for enhancing underground mining projects' economic and environmental results, allowing for a degree of tolerance for systematic deviations. Supplementary Information: The online version contains supplementary material available at 10.1007/s44346-025-00007-2.
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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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".