Artificial Sweeteners Identify Spatial Patterns of Historic Landfill Contaminated Groundwater Discharge in an Urban Stream
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Leachate‐contaminated groundwater from historical municipal landfills, typically lacking engineered liners and leachate collection systems, poses a threat to nearby urban streams, particularly to benthic ecosystems. Effective monitoring and assessment of such sites requires understanding of the spatial patterns (i.e., two‐dimensional footprint) of contaminated groundwater discharge and associated controlling factors. However, discharges from groundwater contaminated by modern wastewater can complicate site assessments. The objectives of this study were to (1) demonstrate the use of artificial sweeteners (AS): saccharin (SAC), cyclamate (CYC), acesulfame (ACE), and sucralose (SUC), to distinguish groundwater discharge areas influenced by historic landfill leachate (elevated SAC and sometimes CYC; low ACE and SUC concentrations) from those influenced by wastewater (high ACE and SUC concentrations), and (2) investigate contaminant discharge patterns for two gaining urban stream reaches adjacent historic landfills at base flows. Contaminant discharge patterns revealed by the AS were strongly controlled by hyporheic flow (low AS concentrations), particularly for the straight reach, and stream sinuosity, particularly for the meandering reach. These patterns were different and the contaminant footprint coverage (<25% of streambed area) much less than most past studies (typically >50% coverage), likely due to the homogeneous streambed‐aquifer conditions and shallow, narrow landfill plume in this setting.
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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 | 0.000 | 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 | 0.001 |
| 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