Assessment of irrigation water quality for the Quebec horticulture industry
Bibliographic record
Abstract
Ready-to-eat vegetables when irrigated with untreated surface water cause risk of gastrointestinal infection to humans.Greenhouse and field studies were conducted to quantify Escherichia coli in the irrigation water and vegetables irrigated with untreated water.The Quantitative Microbial Risk Assessment (QMRA) model used data from the greenhouse and field studies to estimate the health risk to humans on the consumption of irrigated fresh fruits and vegetables.The field study analyzed pathogenic E. coli in the irrigation water during the May-October growing seasons in 2013 and 2014 from two field sites, St-Remi and Rougemont in Quebec.In Rougemont, the maximum concentration of E. coli was found during the May-June period for both years.Whereas in St-Remi, the maximum E. coli concentration was found during the May-June and the September-October.The greenhouse study was conducted in controlled environmental conditions at the Macdonald campus to confirm the level of contamination that was transferred to fruits and soil over a 30 days' time period.The application of E. coli contaminated irrigation water resulted in the contamination of vegetables and of soil using four different treatments.The highest risk for lettuce was observed in the Sprinkler+Organic treatment, followed by the Sprinkler+Mineral and the Drip+Organic treatments, but risk with the Drip+Mineral treatment was observed only on the 20 th day.There was a risk observed in tomatoes only on the 10 th day in the Drip+Organic treatment.The QMRA model used data from field experiments and the combined annual disease burden for all the pathogens was found in the range of 10 -3 to 10 -2 DALYs (Disability Adjusted Life Years) for lettuce and tomatoes.Whereas, the combined gastrointestinal (GI) risk was in the range of 10 -
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".