Criteria-Based Environmental Quality Assessment for Small-Scale Open-Pit Mines (Quarries)
Bibliographic record
Abstract
Mining has great potential for environmental impacts if control and mitigation actions are neglected.Its licensing process is based on environmental and mineral legislation and on the knowledge on possible effects of the pressure from this type of activity on natural resources.The complexity of legal technical requirements, together with particular environmental aspects related to mining activities commonly result in delays in the licensing processes and difficulties in monitoring and mitigation of potential environmental impacts.Here we present and discuss criteria to establish environmental quality indicators for small-scale open-pit mines (SSOPM) that extract sand, clay, limestone, basalt and diabase.The criteria framework, consisting of 65 criteria, was developed using documentary analysis, literature review and expert consultation through the Delphi decision-making method.The main expected result of this study is the development of an environmental quality assessment index, which can be used for monitoring the environmental quality of mining activities, contributing to environmental licensing and to the execution of preventive and remedial actions, and for the guidance of supervisory and licensing bodies as well as by the entrepreneurs themselves.
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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 | 0.017 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".