OGS-GSC collaboration on regional groundwater studies 2014-2019: conclusion
Bibliographic record
Abstract
The Ontario Geological Survey (OGS) and Geological Survey of Canada (GSC) groundwater collaboration in Southern Ontario will be complete at the end of March 2019. The objective of the collaboration was to maximize technical and human resources to meet objectives of the OGS groundwater initiative and the GSC Groundwater Geoscience Program. To that end the initial collaborative effort involved a GAP analysis in March 2015 which provided guidance for aspects of the subsequent 4 year collaboration. In November 2015 a workshop was held with other provincial ministries, conservation authorities and academia to review a path forward on an improved data framework for sustainable groundwater management. The overall project was orientated along the following principal themes i) Framework for Sustainable Groundwater Use, ii) Supporting Great Lakes Water Accords, iii) Methods Development for Regional Groundwater Studies, iv) 4. Case Studies, v) Science and Technology Exchange. Recognizing the extensive work completed as part of provincial Source Protection Program the project focused on development of two regional three-dimensional geological models of the bedrock and surficial geology. These models support a fully coupled regional groundwater - surface-water model being developed with Aquanty Inc. The models are supported by OGS, GSC and other provincial, private sector, and academic work and provide a framework for past and future datasets and groundwater understanding. To support this work a number of data collection studies (reflection seismic, downhole geophysics, chemostratigraphic analysis, hydrochemistry) data collation (Municipal well attributes, OGS section data, borehole logs), and data QA and QC activities were completed. To address concerns about groundwater - surface-water in the Great Lakes Water Accord a conceptual framework was developed as a management guide for watershed practitioners. Methods development focused on a number of areas related to remote sensing and soil moisture downscaling, application of portable X-ray fluorescence spectrometry to determine regional geochemistry, stochastic modelling methods at a watershed scale, and reflection seismic and downhole geophysics. In addition, in the South Nation River watershed a hydrogeophysics study was initiated to investigate the propagation of hydraulic properties through an esker cross-section by the integration of geophysical and hydraulic data within a machine learning environment. A key concern raised in the gap analysis was science and technology communication by the OGS and GSC. In response to that concern an annual open house was initiated in late winter of the four subsequent years and coordinated with Conservation Ontario. This was complemented by coordination with academia on a special issue of the Canadian Journal of Earth Sciences on surficial geology and applications to groundwater. A final summary volume of GSC work will be published in the spring of 2019 as a GSC publication. The OGS and GSC will continue to publish after the formal collaborative project ends, through their respective online sites GeologyOntario, GeoScan, and the Groundwater Information Network (GIN).
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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 | 0.040 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.026 | 0.006 |
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".