A 3-D geologic model of the Paleozoic bedrock of southern Ontario
Bibliographic record
Abstract
The regional 3-D geological model of the Paleozoic bedrock of southern Ontario will be published in 2019. The model encompasses all 110,000 km2 of the western St. Lawrence Lowlands region of south-western and south-central Ontario, except for Manitoulin Island. The model is constructed in Leapfrog© Works (Aranz Geo Limited) - an implicit modelling application, with 56 layers representing 70 Paleozoic bedrock formations, the Precambrian basement, and overlying unconsolidated sediments. Layers were constructed using formation depth data from 26,900 petroleum borehole records in the Ontario Petroleum Data System (OPDS), supplemented by hundreds of deep bedrock boreholes compiled by OGS. Formation depth data in the borehole records comprise the primary data input for the 3-D model. Model layers are based on a new lithostratigraphic chart prepared for this project. A new digital bedrock topography surface has also been constructed and is combined with a new digital subcrop geology map to assemble a grid of 3-D points that approximate and constrain the subcrop surface of each modelled formation and better align the layers with expert knowledge and mapped geology. Model development was an iterative cycle of interim model construction, expert geological appraisal to identify errors/inconsistencies in both the model construction and borehole database, followed by QA/QC editing of formation depth data using well records, geophysical logs, drill cuttings and drill core. QA/QC issues included; incorrect borehole location coordinates, data entry errors, missing / inconsistent / incorrect formation contact picks, sparse data, extrapolation issues beneath Lake Huron, mismatch of digital bedrock topography and bedrock geology, and need for improved data filtering algorithms for calculation of formation bottom depths in individual wells. This project has generated a robust lithostratigraphic model which is a logical next step in the evolution of regional geological mapping. It illustrates the geological connections and continuity between the surface and subsurface; a necessary precursor for understanding hydrogeological links between surface water systems and groundwater, and provides a physical basis for future development of a full hydrostratigraphic model for the area. Other practical applications of the model include; natural resource extraction (e.g., water, gypsum, salt, gas, oil, aggregate), site selection for nuclear waste disposal, exploitation of geothermal energy, public outreach and education, identification of gaps in data and knowledge, and shortcomings in modeling algorithms. Users must recognize that the model is a data-driven algorithmic representation of the actual bedrock geology and is not a substitute for detailed geological mapping. The model is considered a work-in-progress subject to future improvements as new and improved data, modeling software, data processing tools, and geological interpretations become available. The availability of OPDS well database was a critical component in the development of the 3-D model. Model development QA/QC has, in turn, improved the quality of the borehole and related databases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".