Model-Based Integration and Analysis of Biogeochemical and Isotopic Dynamics in a Nitrate-Polluted Pyritic Aquifer
Bibliographic record
Abstract
Leaching of nitrate from agricultural land to groundwater and the resulting nitrate pollution are a major environmental problem worldwide. Its impact is often mitigated in aquifers hosting sufficiently reactive reductants that can promote autotrophic denitrification. In the case of pyrite acting as reductant, however, denitrification is associated with the release of sulfate and often also with the mobilization of trace metals (e.g., arsenic). In this study, reactive transport modeling was used to reconstruct, quantify and analyze the dynamics of the dominant biogeochemical processes in a nitrate-polluted pyrite-containing aquifer and its evolution over the last 50 years in response to changing agricultural practices. Model simulations were constrained by measured concentration depth profiles. Measured (3)H/(3)He profiles were used to support the calibration of flow and conservative transport processes, while the comparison of simulated and measured sulfur isotope signatures acted as additional calibration constraint for the reactive processes affecting sulfur cycling. The model illustrates that denitrification largely prevented an elevated discharge of nitrate to surface waters, while sulfate discharges were significantly increased, peaking around 15 years after the maximum nitrogen inputs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".