Environmental Risks in Open Pit Mines: Representation of a Temporal Evolution Related to Water Factor
Bibliographic record
Abstract
Natural resources are sources of much ecological instability. They are subjects of many types of research and led to the strengthening of measures. However, the exposure to hazards (water-air-soil pollution, radiation, degradation, etc.) due to such industries as mining continuous. This paper intends to show the dynamic relationships between production and time as part of the synergy of the whole extraction system over time. Given to sensitives issues known in the heart of mining operations, water is, therefore, the only environmental factor considered to lighten the research methodology. So, after the hypothesis, a temporal graphic with time and mining production level as explanatory and dependent variables is developed. Then, attention is given to the hypothesis validation used to highlight the joint result of the two variables. This is done by a literature review on environmental management risks tools existing, in-depth on the open pit mines with the simple linear regression analysis. The paired T-test Student result will help to clarify the potential of this statistical approach.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".