Assessment of the Possible Reuse of Extractive Waste Coming from Abandoned Mine Sites: Case Study in Gorno, Italy
Bibliographic record
Abstract
Supply of resources, a growing population, and environmental pollution are some of the main challenges facing the contemporary world. The rapid development of mining activities has produced huge amounts of waste. This waste, found in abandoned mine sites, provides the potential opportunity of extracting raw material. The current study, therefore, focuses on testing the validation of a shared methodology to recover extractive waste from abandoned mines, and applies this methodology to a case study in Gorno, northwest Italy. The methods focused on: (1) analyzing the impact of tailings and fine fraction of waste rock (<2 mm) on plants (Cress - Lepidium Sativum) to assess usability of both as soil additive, and (2) recovering raw materials from tailings and coarse fraction (>2 mm) of waste rock, by means of dressing methods like wet shaking table and froth flotation. The results indicated that the fine fraction of waste rock and tailings did not have detrimental effects on seed germination; however, there was marked decrease in plant growth. As for the recovery of raw materials, the coarse waste rock samples, crushed to <0.5 mm, produced a recovery of Cd, Ga, and Zn—as much as 66%, 56%, and 64%, respectively—using the wet shaking table. The same samples when crushed to 0.063–0.16 mm and used for froth flotation produced a recovery of Cd, Ga, and Zn of up to 61%, 72%, and 47%, respectively. The flotation experiment on tailings showed a recovery of Cd, Ga and Zn at pH 7 of 33%, 6% and 29% respectively. The present investigation highlights the methodologies used for extracting raw materials from extractive waste.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".