Ecological engineering of iron ore tailings into useable soils for sustainable rehabilitation
Bibliographic record
Abstract
Ecological engineering of soil formation in tailings is an emerging technology toward sustainable rehabilitation of iron (Fe) ore tailings landscapes worldwide, which requires the formation of well-organized and stable soil aggregates in finely textured tailings. Here, we demonstrate an approach using microbial and rhizosphere processes to progressively drive aggregate formation and development in Fe ore tailings. The aggregates were initially formed through the agglomeration of mineral particles by organic cements derived from microbial decomposition of exogenous organic matter. The aggregate stability was consolidated by colloidal nanosized Fe(III)-Si minerals formed during Fe-bearing primary mineral weathering driven by rhizosphere biogeochemical processes of pioneer plants. From these findings, we proposed a conceptual model for progressive aggregate structure development in the tailings with Fe(III)-Si rich cements as core nuclei. This renewable resource dependent eco-engineering approach opens a sustainable pathway to achieve resilient tailings rehabilitation without resorting to excavating natural soil resources.
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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".