Distribution and Speciation of Nutrient Elements around Micropores
Bibliographic record
Abstract
In Australia a class of soils known as duplex soils covers approximately 20% of the continent. Their defining characteristic is a sharp texture contrast between the A (or E) and B horizon. The upper B horizon at the point of contact with the E horizon is often highly sodic and of such a high strength that root growth and proliferation, water conductivity, aeration, water storage, and water uptake are restricted. Roots growing in these soils rely on channels created by previous roots or cracks arising from shrink–swell forces associated with seasonal wetting and drying. Although the characteristics of rhizospheres compared with the soil matrix are well documented there is a paucity of knowledge about how long these changes persist after roots decay. This knowledge is fundamental to our understanding of root growth in duplex soils in which plants rely on pore networks formed by previous plants to proliferate in the subsoil. In this study we investigated the heterogeneous chemistry of micropores in situ using synchrotron‐based μ‐x‐ray fluorescence spectroscopy (XRF), μ‐x‐ray absorption near edge structure spectroscopy (XANES), and extended μ‐x‐ray absorption fine structure spectroscopy (EXAFS). The distribution maps of Ca, Mn, Fe, Cu, and Zn at micrometer resolution were collected using μ‐XRF. Subsequently, specific locations with higher concentrations (hot spots) of Mn, Fe, Cu, or Zn were selected and XANES and EXAFS spectra were collected to study the speciation of these elements around the micropore compared with the soil matrix. The μ‐XRF maps showed that Mn was depleted around one of the micropores studied but accumulated around another micropore. Copper and Zn accumulated around the micropores, whereas Ca was predominantly inside micropores. There was no difference between matrix and micropore surface with respect to the distribution of Fe. Around micropores Mn was present in reduced form (Mn II) and Fe was in its oxidized form (Fe III). Manganese and Cu were present in the form of phosphates, Fe as Fe oxides, and Zn as Zn phosphates and adsorbed Zn.
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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 | 0.001 | 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".