A 3-dimensional geological model of the Oak Ridges Moraine area, Ontario, Canada
Bibliographic record
Abstract
Please click here to download the map associated with this article. The Oak Ridges Moraine area, southern Ontario, includes most of the Greater Toronto Area, which is the most populated region of Canada. The ∼ 11,000 km2 region is bounded to the south by Lake Ontario and to the north where Paleozoic bedrock abuts Precambrian Canadian Shield. The area extends 160 km eastward from the Niagara Escarpment, a prominent 100 m high regional bedrock scarp. The surficial sediment is up to 200 m thick, and reveals exposures of the oldest Quaternary sediment in southern Canada. Population growth has caused land use conflicts and increased pressure on groundwater resources. Construction of a regional 3-D geological model of the glacial stratigraphy was needed to support a better understanding of aquifer distribution, scale, and resource potential and protection. Mapping of the regional glacial geomorphology and sediment succession identified a number of distinct landforms: tunnel channels, drumlins, eskers, moraines, and till and lacustrine plains. Using sequence stratigraphic concepts, strata have been grouped into four principal units that unconformably overlie Paleozoic bedrock: Lower sediment, Newmarket Till, Oak Ridges Moraine, and Halton Till. These four Quaternary units plus bedrock have been mapped in the subsurface as a succession of interpolated surfaces using an innovative stratigraphic database-GIS approach. The model-building process involved stratigraphically coding high-quality data, then integrating an extensive and diverse array of subsurface geological and archival datasets using an expert system (geological rules). Stratigraphic data subsets were then extracted and merged with DEM-controlled surface mapping and interpolated in a GIS.
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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 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".