Impact of Mining Activity upon Environment in Roşia Montană
Bibliographic record
Abstract
Roşia Montană is the greatest gold ore in Romania and one of the greatest in Europe, and its exploitation has been carried out since Antiquity up to nowadays. If the traditional extraction and processing technologies had a minimal impact upon environment, the ones adopted in modern times have affected all the components of the natural environment. In the perspective of capitalizing the gold ore through the programme elaborated by the Canadian company, Gold Corporation, the zonal geographical space will be degraded up to the level of industrial dessert over an area of 100 km2 and in case of damage, the affected area can extend enormously. The environmental problems are related both to the specific nature of such an industrial activity and, especially, to the use of enormous quantities of sodium cyanide directly on the preparation flux from the industrial plant. Few such cases are known worldwide, in several economically less developed countries. Usually, cyanides are used for treating the gold concentrations, operation done in conditions of maximum security, in closed spaces, situated in isolated zones and the neutralization (detoxification) of cyanides is done in situ. The treatment of cyanides in open spaces has always generated environmental problems. Moreover, none of the cyanide treatment technologies eliminates entirely their toxic effect (less toxic chemical products are obtained). In order to avoid the production of an environmental disaster and to preserve the local patrimony values (in this place there lies the richest mining archeological site in Europe), we elaborated several recommendations we consider feasible as they allow both the capitalization of ore, which is a socio-economic necessity of the area, and the ecological reconstruction of the affected geographical space.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".