Subsurface heterogeneity in the geological and hydraulic properties of the hummocky Paris Moraine, Guelph, Ontario
Bibliographic record
Abstract
The advance and retreat of ice lobe margins of the Laurentide Ice Sheet formed moraines that are a prevalent feature throughout southwestern Ontario. In contrast to the well-studied stratified moraine complexes, recessional and end moraines have largely been ignored in the context of hydrogeological studies. Recent urban growth has led to development pressures on these moraines and a need to better understand their hydrogeology. This study presents data sets from the Paris Moraine near Guelph, Ontario, to examine its geomorphology, internal composition, and the corresponding hydraulic properties of these ice-marginal features. The moraine’s geomorphic elements were mapped using high-resolution Global Positioning System transects, aerial photograph analysis, and ground truthing. Nine continuous sediment cores were recovered to determine the nature and distribution of subsurface sedimentary units and their relation to the regional stratigraphic framework. Cores were described in detail using standard sedimentological techniques, and significant sediment heterogeneity was observed in cross sections. Grain-size analyses of over 150 samples provide site-specific estimates of saturated hydraulic conductivity. In addition, saturated hydraulic conductivity was measured on 104 samples using the falling head permeameter method. This study found that different scales of sediment heterogeneity occur across the moraine and the associated till plain and outwash. In contrast, the hydraulic conductivity varies much less. It is expected that certain sedimentary units at specific depths will impact groundwater flow at the centimetre to hundreds of metres scale, which is significant in environmental site assessments or for understanding contaminant hydrogeological problems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".