Assessment of Vertical Hydraulic Connectivity in a Multilayered Aquifer-Aquitard System in Response to Deep Bedrock Pumping Using High-Resolution Spatiotemporal Monitoring
Bibliographic record
Abstract
This study investigates a multilayered fractured bedrock aquifer-aquitard system overlain by complex moraine and ice-marginal deposits in Guelph, Ontario where a new bedrock municipal supply well is proposed adjacent to a provincially significant wetland as a complement to an established municipal well field. The main objectives of this study are to assess the vertical hydraulic connectivity and potential hydrologic impacts across the multi-layered bedrock and overlying Quaternary sediments through an improved conceptualization of hydrostratigraphic units within the complex lithostratigraphic sequence in response to a 30-day pumping test. Multiple high-resolution datasets collected in one bedrock borehole and four Quaternary boreholes were used to inform the design and installation of custom-built multi-port systems instrumented with pressure transducers for continuous monitoring of hydraulic head. Regression deconvolution was used to separate multiple anthropogenic and natural signals from the water level data and generate constant rate pumping response functions, which were used to determine and interpret the hydraulic responses to pumping. This research will support decisions regarding the municipal well capture zone and sustainable pumping rate to minimize impacts to shallow groundwater and the natural environment.
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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 | 0.000 | 0.001 |
| 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".