Micro topography, organic amendments and an erosion control product for reclamation of waste materials at an arctic diamond mine
Bibliographic record
Abstract
Building a suitable soil is the foundation for successful revegetation and ecosystem development following disturbance. Mines produce large amounts of waste materials, which are important resources for soil building where it is lacking, although their potential on their own to support plants is often low. The objective of this research was to evaluate the effectiveness of built micro topography, organic amendments and an anionic polymer erosion control product (Soil Lynx) in improving plant community establishment on substrates of diamond mine waste materials (crushed rock, processed kimberlite, lakebed sediment) in the Northwest Territories, Canada. In general, micro topography and organic amendments worked independently to enhance revegetation. Built micro topography only enhanced plant establishment on processed kimberlite with highest plant density, cover and height in depressions. Plant response was considerably less on this substrate than on the others. Crushed rock had at least eight times the plant density and cover of processed kimberlite and double that of lakebed sediment. Sewage sludge incorporated 5–10 cm into surface substrates significantly improved plant establishment, growth and frequency of seed heads. Soil Lynx provided no benefit for plants. After 4 years, crushed rock with sewage sludge showed the greatest potential for use in reclamation. Seeded grasses dominated all treatments, although moss and lichen cover were increasing with time on crushed rock. Gravel disturbances are common in arctic regions and the ability to accelerate plant community development through use of novel soil building materials can ensure ecosystem resilience.
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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 | 0.000 | 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) | 0.002 | 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 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".