The Oak Ridges Moraine Aquifer System, Canada: Data-driven Collaborative Science for Public Purpose
Bibliographic record
Abstract
The Oak Ridges Moraine is an upland landform extending approximately 160 km in an east-west direction over much of south-central Ontario, Canada. Geologically this part of Ontario is characterized by Quaternary-aged sediments deposited over the last approximately 130,000 years overlying Paleozoic bedrock largely consisting of shale and limestone. Aquifer complexes within and beneath the moraine provide drinking water to hundreds of thousands of people and provide source water to streams which headwater along the moraine flanks. These streams provide key habitat for healthy functioning ecosystems. The study area is dominated by agricultural land use activities interspersed with urban centers (e.g., City of Toronto). Challenges to water resource management and ecosystem protection include increasing urban population and urbanized areas, climate change (increased severe weather events including flooding), and water quality impairment from many anthropogenic land use activities (e.g., road salt, pesticides, nutrients, PFAS). This book describes the geology and hydrogeology of the area, and the development and refinement of the conceptual model of flow system understanding. This knowledge and understanding have been applied to various water management initiatives that exist within the study area. A unique aspect of this book is its link to the Oak Ridges Moraine Groundwater Program (ORMGP), a partnership of local government agencies that collaboratively manage, analyse and make readily available hydrogeological information via an interactive online mapping website. The overall program goal is that Ontario learns from earlier work, and that water related decisions continually improve, having been made using reliable data and interpretations.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.005 |
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".