Assessing sources of nitrate contamination in the Shiraz urban aquifer (Iran) using the δ<sup>15</sup>N and δ<sup>18</sup>O dual-isotope approach
Bibliographic record
Abstract
Nitrate ([Formula: see text]) is one of the major threats to the quality of the drinking water taken from the Shiraz aquifer. This aquifer undergoes high anthropogenic pressures from multiple local urban (including uncontrolled sewage systems), agricultural and industrial activities, resulting in [Formula: see text] concentrations as high as 149 mg L(-1), well above the 50 mg L(-1) guideline defined by the World Health Organisation. We coupled here classical chemical and dual isotope (δ(15)N and δ(18)O of [Formula: see text]) approaches trying to characterize sources and potential processes controlling the budget of this pollutant. Chemical data indicate that nitrate in this aquifer is explained by distinct end-members: while mineral fertilizers isotopically show to have no impact, our isotope approach identifies natural soil nitrification and organic [Formula: see text] (manure and/or septic waste) as the two main contributors. Isotope data suggest that natural denitrification may occur within the aquifer, but this conclusion is not supported by the study of other chemical parameters.
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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 | 0.001 | 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".