Agroenvironmental Determinants Associated with the Presence of Antimicrobial‐resistant <i>Escherichia coli</i> in Beach Waters in Quebec, Canada
Bibliographic record
Abstract
Exposure to microorganisms resistant to antimicrobials may constitute a health risk to human populations. It is believed that one route of exposure occurs when people engage in recreational activities in water contaminated with these microorganisms. The main objective of this study was to explore population-level and environmental determinants specifically associated with the presence of antimicrobial resistant (AMR) generic Escherichia coli isolated from recreational waters sampled from beaches located in southern Quebec, Canada. Water samples originated from the Quebec provincial beach surveillance program for the summers of 2004 and 2005. This study focused on three classes of determinants, namely: agricultural, population-level and beach characteristics for a total of 19 specific factors. The study was designed as a retrospective observational analysis and factors were assessed using logistic regression methods. From the multivariable analysis, the data suggested that the percentage of land used for spreading liquid manure was a significant factor associated with the presence of AMR E. coli (OR=27.73). Conceptually, broad factors potentially influencing the presence of AMR bacteria in water must be assessed specifically in addition to factors associated with general microbial contamination. Presence of AMR E. coli in recreational waters from beaches in southern Quebec may represent a risk for people engaging in water activities and this study provides preliminary evidence that agricultural practices, specifically spreading liquid manure in agricultural lands nearby beaches, may be linked to the contamination of these waters by AMR E. coli.
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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 | 0.000 | 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 | 0.001 |
| 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".