Solubility and Lability of Copper in a Copper-Mine Tailings Treated with Two Organic Amendments
Bibliographic record
Abstract
Copper-mine tailings contain considerable amounts of copper (Cu) that may be extracted biologically or by organic ligands and may then become available to plants.A laboratory incubation experiment was conducted to assess the effect of a commercial garden growth substratum (GGS) containing natural mycorrhizae (Glomus intraradices) and peat moss in combination with lemon peel waste (LPW) on the evolution of labile Cu pool with time in a slightly alkaline Cu-mine tailing containing calcite.There were eight treatments combining four rates (0, 12.4, 50 and 100 g GGS kg -1 tailings) and two rates (0 and 100 g LPW kg -1 tailings).The amendments were thoroughly mixed with air-dry tailings in plastic bags.Distilled water was added to maintain the substrate at field capacity throughout the 8-week incubation period.The amounts of labile Cu in tailings increased with incubation time.Extractable Cu fractions as labile Cu (DTPA, Mehlich-3) were significantly increased after adding GSS and LPW.The smallest amount of labile Cu was found in the unamended tailings and the highest amount in the GGS-amended tailings.
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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 | 0.000 | 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) | 0.001 | 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".