Using hydrogeologic context and water budgets to evaluate the potential for groundwater contributions to contaminants in Lake Superior
Bibliographic record
Abstract
This study presents a synthesis of the hydrogeology in the U.S. Lake Superior watershed and the contribution of groundwater to the water budget of the U.S. Lake Superior basin. Much of the shoreline of Lake Superior in Minnesota and Michigan is composed of hydrogeologic units contributing very little direct groundwater discharge to the lake. Groundwater in watersheds adjacent to the lake typically flows in short, local flow systems characterized by thin glacial sediments with active groundwater flow in fractured bedrock within the top 60–90 m below land surface. The complex groundwater system in Wisconsin’s Bayfield Peninsula has the largest groundwater reservoir near the lake, characterized by thick sand and gravel glacial deposits and underlying sandstone aquifer. Although these thick sandy glacial deposits are not in direct contact with the lake at the shoreline, groundwater discharge may still be significant via subsurface exposures beyond the shoreline or flow through the underlying sandstone aquifer. Overall, most groundwater in the watershed is contributed as indirect base flow in streams around the lakeshore and comprises about 60 percent of the upland water budget. Direct groundwater flow to the shoreline contributes 2 to 9 percent of the inflow. Identifying possible contamination sources through direct sampling of groundwater would be an inefficient way to detect problems if sources are unknown, particularly for some chemicals of concern such as PFAS, pesticides, PCBs, chloride, and nutrients. Evaluating the chemical characteristics of contamination is also important to consider in evaluating how groundwater may contribute to pollution in Lake Superior.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".