Farm Well Water Quality in Alberta
Bibliographic record
Abstract
Abstract On-farm groundwater supplies in Alberta were evaluated for chemical (routine chemistry, trace metals), herbicides and microbiological (total and fecal coliforms) parameters to determine the suitability of domestic drinking water usage based on the Guidelines for Canadian Drinking Water Quality (GCDWQ). The sampling program was conducted between May and October of 1995 and 1996. Thirty-two percent of the 816 farm water wells surveyed (depth range 2 to 284 m) exceeded the GCDWQ for maximum acceptable concentration (MAC) or interim maximum acceptable concentration (IMAC) of at least one parameter. In addition, the water from 92% of the sites exceeded the GCDWQ for at least one of the aesthetic objectives (AO). The chemicals were ranked from most to least frequently exceeding the GCDWQ MAC, in the following order: F >> NO3 −N + NO2−N > As > Se > Pb > B > U > Cr (13, 6, 3, 3, 2, 0.9, 0.4 and 0.2% of all samples, respectively). The parameters ranked from most to least frequently, exceeding the AO, in the following order: TDS > Na > Fe > Mn > pH > SO4 > Cl > Al > Zn > Cu (85, 64, 36, 34, 23, 19, 6, 2, 1 and 0.1 % of the samples, respectively). The majority of the higher concentrations of most inorganic parameters are due to natural geological conditions defined by source aquifer mineralogy. The effects of primary agriculture are likely limited to the 3% herbicide detections and to some nitrate and microbiological contaminations observed; this water should not be used for human consumption without some form of site-specific treatment. Some rural residents may be “mistreating” their water, and a general lack of water testing among rural residents was noted.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".