Data capture, consolidation and reclassification: moving toward a geological framework to support groundwater management in southern Ontario
Bibliographic record
Abstract
Numerous reports and reviews of groundwater management in Canada, and more specifically in Ontario, have identified the need for the capture and consolidation of data within more structured and accessible database formats with online availability. There remains an enormous amount of valuable legacy geoscience data available in hardcopy and scanned PDF format and more recent work that is primarily available in PDF files. In the past year the GSC has collaborated with the Ontario Geological Survey (OGS), Ministry of Environment and Climate Change (MOECC), Ministry of Natural Resources and Forestry (MNRF), and conservation authorities toward this end. Activities have focused on the data capture, consolidation and classification of data sets collected under the Drinking Water Source Protection Program, legacy municipal and conservation authority information on municipal wells, non-digital legacy data of the OGS and GSC, consolidation of OGS and GSC published work and OGS-GSC geophysical data sets. Work was also completed on enhancing the geological content of the Provincial Groundwater Monitoring Network. Much of this information has been entered into a relational database; however, much of it remains in flat files and requires additional iterative QA/QC before it is suitable for dissemination online. The most extensive effort was expended on the capture and consolidation of aquifer parameter information tied to municipal wells. Initial efforts focused on Source Protection (SP) reporting available online and expanded to include 19 report types of which 8 were associated with SP and 11 are reports types that may predate SP but support municipal water supplies. To-date approximately 500 reports have been reviewed with 946 municipal wells identified in 32 SP areas, with cross indexing of 84% of the wells with the WWIS and 97% with the PTTW database. Information was assembled on over 30 attributes in 5 general groupings that capture well information. Based on the reports reviewed, 399 aquifer entries, preliminary grouped into 213 aquifers units have been tabulated. Both the GSC and OGS have legacy hardcopy data holdings that are beig scanned, commonly to a PDF format. This nevertheless leaves the laborious task of capturing pertinent information for consolidation in a database structure. Two distinct activities have been undertaken, i) the capture of legacy section descriptions and analytical data from reports, and ii) consolidation of digital information from standalone publications into a single database. The focus of this activity has been on data that will support the stratigraphic classification necessary for 3-D geological modelling. Additionally two GSC datasets have been consolidated the downhole geophysical data and reflection seismic data. As part of an ongoing national data compilation new borehole geophysics data collected with the OGS has been integrated into the national dataset. Additionally for the first time reflection seismic data has been consolidated into a database structure bringing together 10 years and hundreds of km of seismic data, of which approximately 20 percent is in southern Ontario. An ongoing challenge is to complete the necessary QA/QC on the datasets and making them available online. It is anticipated that with the retooling of the Groundwater Information Network (GIN) to the GWML 2.0 standard much of this information will be able to be displayed in the coming 18 months.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.011 | 0.025 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".