Clay minerals and phosphate sorption in soils
Bibliographic record
Abstract
Solubilization of soil phosphate accumulated during the last decades in fertilized soils can be profitably used to decrease phosphate (PO4) fertilization while maintaining crop production. In this respect, it is important to clearly identify and rank the different soil constituents regarding their importance for the control of PO4 sorption. However, the relative importance of clay minerals versus Fe oxide-hydroxides is still controversial. Indeed, some researchers only considered the influence of Fe oxide-hydroxides, while others also included clay minerals in their PO4 sorption models. Through this communication our main objective is to present a set of evidences issued from the literature and also based on original data which support the significant influence of clay minerals on PO4 sorption in soils. The first evidence is based on the adsorption capacity of minerals and on the mineralogical composition of soils. Second, we showed that the adsorption properties of clay minerals versus pH do not resemble to that of Fe oxide-hydroxides, thus precluding the consideration of Fe oxide-hydroxides as a surrogate for clay minerals. Last, preliminary results of synchrotron-based X-ray absorption spectroscopy at the phosphorus K-edge showed that PO4 binding to clay minerals substantially involves structural Al-O sites and not only Fe-O sites. To conclude, both Fe oxide-hydroxides and clay minerals should be considered in PO4 retention modelling in soils as they considerably influence sorption processes.
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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 | 0.004 | 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 | 0.001 | 0.002 |
| 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".