Nitrification and nitrogen mineralization in agricultural soils contaminated by copper mining activities in Central Chile
Why this work is in the frame
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Bibliographic record
Abstract
Microbiological bioassays of nitrification and nitrogen mineralization have been used for evaluation of soil quality on metal-contaminated soils.We evaluated the effectiveness of nitrification and nitrogen mineralization bioassays as quality indicators of soil degradation caused by metal contamination.We performed standard tests based on protocols of ISO 14238 (2012) and ISO 15685 (2012) on 90 soil samples collected from agricultural areas in central Chile that were historically contaminated by mining activities.Potential nitrification rate (PNR) was best explained by pH and organic matter content (OM) (R 2 =0.32), while nitrogen mineralization (Nmin) was best explained by OM and clay content (R 2 =0.44).Following normalization of the bioassays responses with respect to OM yielded significant correlations between PNR and pH and total Cu content (R 2 =0.22), and between Nmin and clay and total Cu contents (R 2 =0.19).However, inasmuch as total Cu content improved the regression model showing the inhibitory effect of Cu in both bioassays, it accounted for a mere small proportion of the variance.This was despite the wide range of Cu contents in the soils studied (51-2878 mg kg -1 ).Hence, due to the known sensitivity of the nitrification and nitrogen mineralization process to physicochemical characteristics of soils, these bioassays seem to have limited applicability for metal toxicity assessment in metalcontaminated soils.
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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 | 0.001 | 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 | 0.001 |
| 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 it