Bibliographic record
Abstract
Geoscience is a relatively new program area for many Conservation Authorities (CA); it wasn't until about 2001 that CAs started to employ Geoscientists. Initial CA geoscience programs consisted of the newly formed Provincial Groundwater Monitoring Network (PGMN) and the Source Water Protection (SWP) Program. The Geoscience services offered by CAs has evolved and is now more integrated into regular CA business and has opened up additional opportunities for collaborations with municipal, provincial, and federal partners. In 2008 the CA Geosciences Group was formed to ensure consistency between CAs for the application of geoscience among CAs. Of the 36 CAs approximately 14 CAs currently employ qualified geoscientists, the remaining 22 contract out geosciences work as required. This presentation will look at how geoscience has been integrated into the core CA business, which includes 1. Aspects of planning and development review; review and commenting on public policy and regulations; 2. Watershed Plans, including the watershed Report Cards; 3. Monitoring programs including the PGMN, soil moisture, and climate change; 4. The SWP program that helped to advance groundwater information in Ontario through the water budgets and modeling exercises; 5. Other modeling including the Conservation Authorities Moraine Coalition's YPDT 3-D model; 6. Participation in special projects for the development of a Low Water Response groundwater indicator and soil moisture; 7. Participation in the development of the annex 8 groundwater report under the Great Lakes Water Quality Agreement; and 8. Partnerships with the Ontario Geological Survey investigating locally important geologic features that have an impact on water quantity and quality.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.293 | 0.051 |
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".