Extent and Mechanism of Interaction between Phosphate and Citrate in a Calcareous Soil
Bibliographic record
Abstract
Core Ideas Modification of Ca levels influences P adsorption. Citrate influences the adsorption equilibrium of P onto soil. Competitive adsorption of citrate and P is primary mechanism of interaction. In subsurface systems that have been contaminated with petroleum hydrocarbons (PHCs), the degradation by microbes is limited by nutrient availability, primarily by bioavailable phosphorus (P). Low‐molecular‐weight organic acids (LMWOA), particularly citrate, have been proposed as a remediation amendment to enhance P mobility, but the effect of citrate on P retention by calcium‐rich soils is poorly understood. In this study, the sorption of P in the absence and presence of citrate on calcareous cold soils was investigated under controlled laboratory conditions using a combination of laboratory‐based adsorption and desorption studies and synchrotron‐based spectroscopic techniques. The results indicate that calcium exerts a strong control on P sorption by forming calcium phosphate minerals, thus limiting the availability of P for transport or microbial uptake. Treatments that reduce reserve and exchangeable Ca increase the relative proportion of adsorbed P. When citric acid is also added to these calcareous soils, their buffering capacity largely inhibits any desorption of P or changes in P speciation until citrate levels exceed P additions by more than 10 to 1. By increasing citrate to P ratios to between 10:1 and 50:1, it is possible to overcome the soil's buffering capacity, decrease pH, and enhance P desorption via competition with citric acid. This suggests that one can enhance P transport in this soil system, but only when the citrate to P ratio is properly adjusted for the site's Ca levels.
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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) | 0.000 | 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 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".