Anthropogenic Impacts on a Bedrock Aquifer at the Village Scale
Bibliographic record
Abstract
This study focuses on assessing groundwater potability in a highly complex and heterogeneous fractured bedrock aquifer having variable overburden cover. Eight monitoring wells were installed in a privately serviced lakeside village, and groundwater was routinely sampled over a 2-year timeframe for concentration analysis of nitrate, fecal indicator bacteria, stable isotopes, and a total of 41 pharmaceutical compounds. While pollutant concentrations remained low throughout the study, the presence of fecal indicator bacteria and pharmaceuticals was noted at least once (but not always consistently) in most sampling intervals. An interpretation based on the integration of chemical, bacterial, and site characterization datasets suggests that: (1) the fracture network is complex and heterogeneous with limited vertical connectivity; (2) existing pathways are sufficient for the quick and widespread migration of surface contaminants to depth; (3) anthropogenic contaminants from both septic systems and agriculture are likely sourced in the surrounding uplands where overburden is thin; and (4) fecal contamination, as observed over the long term, is ubiquitous at the village scale. Groundwater quality is continually changing in this hydrogeologic environment and the determination of potability on the larger scale is not likely to be adequately captured with infrequent domestic well sampling (i.e., voluntary annual sampling by homeowners).
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".