Assessment of the microbial quality of irrigation water in a prairie watershed
Bibliographic record
Abstract
AIMS: To assess levels of faecal contamination in the Qu'Appelle River (Saskatchewan, Canada) and its suitability for irrigation, by using the Colilert-18/Quanti-Tray technology. METHODS AND RESULTS: Various sites located along the Qu'Appelle River were sampled weekly from May to August 2005-2007. A total of 594 freshwater samples were collected and analysed for enumeration of Escherichia coli using the Colilert-18. The false-positive rate for E. coli detection using Colilert-18 was at most 1.5%. Throughout the irrigation period (June to August), up to 85% of the water samples collected from one of the irrigation water-pumping sites exceeded the recommended limit of 100 CFU per 100 ml. Spikes in E. coli counts were generally concomitant with the sudden rise in river flows. A sub-sample of confirmed E. coli isolates were typed by randomly amplified polymorphic DNA (RAPD). RAPD analysis revealed a high degree of genetic diversity among E. coli isolates. A significant association between RAPD patterns and the month of E. coli isolation was demonstrated. CONCLUSIONS: Colilert-18 provides an effective means for assessing microbial quality of irrigation water. SIGNIFICANCE AND IMPACT OF THE STUDY: Qu'Appelle River is subject to variability of faecal contamination during irrigation times and monitoring throughout irrigation season is important for ensuring safe production practices.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".