Influence of biosolids and fertilizer amendments on physical, chemical and microbiological properties of copper mine tailings
Bibliographic record
Abstract
A 3-yr field study was conducted on two texturally different tailings sites at the Highland Valley Copper Partnership mine in south-central British Columbia to determine the effects of fertilizer and biosolids amendments on selected soil physical, chemical and microbiological properties. Soil bulk density and penetration resistance decreased in the upper 15 cm of tailings with increasing dry biosolids application rates of 50, 100, 150, 200 and 250 Mg ha-1. The addition of biosolids increased gravimetric water retention at field capacity and wilting point, but no significant changes occurred in the gravimetric water-holding capacity as both field and wilting point increased proportionally. Increasing biosolids decreased volumetric water-holding capacity on the silt loam, but had no effect at the sandy site because of decreased bulk density. Soil pH was not impacted by the treatments while electrical conductivity, soil organic matter, total carbon and cation exchange capacity increased with increasing levels of biosolids applied. Biosolids enhanced biological activity by increasing total aerobic, total anaerobic, iron reducing, sulfate reducing and denitrifying microorganisms near the surface. The fertilizer amendment did not alter soil physical or chemical properties from those of the control. The addition of biosolids was more effective at enhancing properties related to soil quality and fertility and therefore more effective for building soil organic matter on reclaimed tailings sites than the traditional use of inorganic fertilizer.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 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".