Nitrogen-Rich Organic Matter Formation and Stabilization in Iron Ore Tailings: A Submicrometer Investigation
Bibliographic record
Abstract
Organic matter (OM) formation and stabilization are critical processes in the eco-engineered pedogenesis of Fe ore tailings, but the underlying mechanisms are unclear. The present 12 month microcosm study has adopted nanoscale secondary ion mass spectrometry (NanoSIMS) and synchrotron-based scanning transmission X-ray microscopy (STXM) techniques to investigate OM formation, molecular signature, and stabilization in tailings at micro- and nanometer scales. In this system, microbial processing of exogenous isotopically labeled OM demonstrated that 13 C labeled glucose and 13 C/ 15 N labeled plant biomass were decomposed, regenerated, and associated with Fe-rich minerals in a heterogeneous pattern in tailings. Particularly, when tailings were amended with plant biomass, the 15 N-rich microbially derived OM was generated and bound to minerals to form an internal organo-mineral association, facilitating further OM stabilization. The organo-mineral associations were primarily underpinned by interactions of carboxyl, amide, aromatic, and/or aliphatic groups with weathered mineral products derived from biotite-like minerals in fresh tailings (i.e., with Fe 2+ and Fe 3+ ) or with Fe 3+ oxyhydroxides in aged tailings. The study revealed microbial OM generation and subsequent organo-mineral association in Fe ore tailings at the submicrometer scale during early stages of eco-engineered pedogenesis, providing a basis for the development of microbial based technologies toward tailings’ ecological rehabilitation.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".