Integrated hydrogeological and geophysical study of depression‐focused groundwater recharge in the Canadian prairies
Bibliographic record
Abstract
In the northern prairie region of North America, numerous seasonal wetlands and ephemeral ponds form as snowmelt water is trapped in small topographical depressions. A detailed hydrogeological investigation is combined with electrical resistivity imaging (ERI) to evaluate the roles of the wetlands and ponds on depression‐focused groundwater recharge at the St. Denis National Wildlife Area in Saskatchewan, Canada. The analysis of groundwater samples indicated two distinct geochemical zones: a zone of salt leaching under Wetland 109 and zones of salt accumulation under the adjacent uplands. Two intermediate zones were identified as partially leached or mixed leached‐unleached and premodern or mixed saline‐nonsaline water. The resistivity images of the areas around 109 were classified using the correlation between ERI‐derived electrical conductivity (EC) and the groundwater EC. The ERI data clearly showed that depression‐focused recharge occurs under all depressions regardless of size. Leaching is observed to the depth of a regional intertill aquifer, indicating that depression‐focused recharge contributes to the regional groundwater system. The ERI data also revealed the complex pattern of salt distribution that could not have been recognized by hydrogeological observations alone. The complex distribution of salts appears to be caused by interaction between wetlands and variations in topography.
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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 | 0.002 |
| 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) | 0.000 | 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".