Impacto de la transformación digital en la minería subterránea peruana
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Currently, an evident change has been noticed regarding the digital transformation of production processes as a result of the fourth industrial revolution, as well as COVID-19, which have shown how remote work and process optimization greatly influence in productivity. The mining sector is no exception, since in countries like Chile, Europe and Canada, they have automated operations, avoiding risks and damage to the health of workers. Thus, underground mining, being a method widely disseminated and applied in mining activity in Peru, presents challenges compared to the traditional method, so great technological advances are not yet evident. That is why this research is a study of the impact of digital transformation on the productivity of Peruvian underground mining, for which the main advantages and disadvantages of this type of mining in Peruvian territory were diagnosed; The challenges of underground technologies so that they can be used were examined and a case study was analyzed to establish the impact of the technology. In addition, it aims to improve the productivity of the company studied. The hypothesis raised in this analysis is that the implementation of technology focused on digital transformation increases productivity in underground mining. Based on the case study, it is concluded that underground mining, within the NEXA company, has noticed how the digital transformation has represented a control and increase in production.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.004 | 0.003 |
| 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