Solubility, partitioning, and activity of copper‐contaminated soils in a semiarid region
Bibliographic record
Abstract
Abstract We studied the fate of Cu in contaminated semiarid soils from two areas with different mining activities in central Chile. Several regression models were evaluated to use soil physicochemical characteristics to predict solubility, partitioning, and activity of Cu. Furthermore, we hypothesize that the type of Cu mining compound (smelter dust versus tailing sand) can be another important variable determining the bioavailability of Cu. In the studied neutral to alkaline soils, soil organic matter (SOM) enhanced Cu solubility most probably through the formation of organic complexes with dissolved organic C (DOC). As a consequence, Cu solubility and partitioning were better explained by DOC concentration than by SOM content. On the other hand, Cu activity was mainly related to soil pH and was not affected by DOC. Although we found differences between the two study areas, Cu solubility and partitioning might not be as dependent upon the origin of the Cu mining compound as upon other physiochemical characteristics that influence the concentration and characteristics of DOC. Total Cu, pH, and DOC would be the most important variables to consider on Cu solubility, however, data about the nature of SOM may certainly improve the prediction models. Thus, multiple binding site models between Cu and DOC should be studied to improve predictions of Cu solubility.
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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 | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".