Environmental effects of copper mine tailings reclamation with biosolids
Bibliographic record
Abstract
Anaerobically digested biosolids (treated sewage sludge) were applied to Copper mine tailings (pH 8.0) in Princeton, B.C. to determine how well biosolids could achieve land reclamation on a site prone to wind erosion in a semi-arid climate (350 mm mean annual precipitation). In October 1992, biosolids at 62, 77 (two plots), and 179 Mg/ha were applied to four 0.5 ha plots with manure spreaders. In 1993, vegetation established on all sites without irrigation which reduced wind erosion. The 77 Mg/ha treatment led to the best vegetation quality and yield in the first growing season. Yield increased from 300 kg/ha (Control) to 5500 kg/ha (77 Mg/ha). In October 1993, additional biosolids were applied to the 62 and one of the 77 Mg/ha plots to test if it is beneficial to apply biosolids in two applications rather than one larger application. Yields in 1994 were generally lower than in 1993 reflecting lower precipitation. Alfalfa established well on all sites and was the dominant legume while brome and fescue were dominant grasses. Vegetation samples showed no micronutrient or metal toxicity problems. Notable trends in both growing seasons included: foliar Mo concentrations were lower; foliar Cu:Mo ratios were higher; cattle and deer grazing did not hamper growth; soil pH decreased whereas concentrations of Total P, Bray-P, TKN-N, NH₃-N, NO₃-N, Fe, and Hg increased with increasing application rates. Nitrate below 60 cm was negligible for all plots except the 179 Mg/ha and split application plots in 1994. N leaching losses were below 4-8% of applied TKN-N. Metal concentrations were below the CCME criteria for agricultural and residential soils except for Cu. Well water samples met the Canadian Drinking Water Guidelines.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".