Investigation of the Potsdam Group sandstone aquifer vulnerability with the DFN-M approach
Bibliographic record
Abstract
As cities grow, surrounding rural communities often experience development stresses such as increased demand on local aquifers. Rural aquifers can have different threats than city centres, such as nitrates from agriculture or pathogens related to septic systems that may not have historically been a dominant concern, but become so under the increased water demands. Case in point is the growing community of Greely, near Ottawa, Ontario which is surrounded by agricultural lands, homes have individual septic systems, and a shallow bedrock aquifer provides the sole water supply from a communal well. The City of Ottawa has engaged the project team to examine the deeper Nepean sandstone as an alternative water supply. An initial borehole was continuously cored through the Paleozoic bedrock sequence into the Precambrian close to the existing pumping well. The detailed Discrete Fracture Network - Matrix (DFN-M) approach was applied including rock core logging, chemical analysis, geophysical logging, hydrogeologic and hydro-geophysical testing, with cross-hole testing pending. We present the study approach, preliminary results and future plans. In addition to dealing with Greely's challenges, the multiple high-resolution data sets provide insight into this complex geologic/hydrogeologic setting and an initial assessment of the sandstone's viability as a water supply elsewhere.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".