Amendments to improve plant response under simulated water-limited conditions in diamond mine Anthroposols
Bibliographic record
Abstract
Development of Anthroposols for land reclamation requires consideration of a variety of factors to support plant establishment and growth. Water limitation is a key challenge when using mine waste as a growth medium, and these materials also have poor structure and lack organic matter and nutrients. These greenhouse experiments assessed effectiveness of treatments composed of hydrogel and organic amendments to increase plant establishment and growth under water-limited conditions in mine waste materials (crushed rock, lakebed sediment, and processed kimberlite) from a diamond mine in northern Canada. Amendments were hydrogel, peat, sewage, and soil, mixed with waste materials (substrates) at four application rates, and seeded with slender wheat grass (Elymus trachycaulus). One experiment assessed germination response with limited watering during germination, and the other experiment assessed growth response with adequate water during germination followed by restricted water. Substrate had the greatest effect on germination, with processed kimberlite and crushed rock being most successful, at least 10% higher than lakebed sediment. Sewage amendment resulted in the largest plants (mean 0.22 g in lakebed sediment, 0.40 g in crushed rock and processed kimberlite, 0.05 g no amendment); sewage had a limited effect on germination. Highest organic amendment application generally improved plant response. Hydrogel did not improve plant growth, although it increased germination up to 63% in processed kimberlite. Type of mine waste, amendment, and rate of application impacted germination and plant growth and can be altered to build a suitable Anthroposol for reclamation.
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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".