Antimicrobial‐Resistant <i>Escherichia coli</i> in Public Beach Waters in Quebec
Bibliographic record
Abstract
INTRODUCTION: Human exposure to antimicrobial-resistant bacteria may result in the transfer of resistance to commensal or pathogenic microbes present in the gastrointestinal tract, which may lead to severe health consequences and difficulties in treatment of future bacterial infections. It was hypothesized that the recreational waters from beaches represent a source of antimicrobial-resistant Escherichia coli for people engaging in water activities. OBJECTIVE: To describe the occurrence of antimicrobial-resistant E coli in the recreational waters of beaches in southern Quebec. METHODS: Sampling occurred over two summers; in 2004, 674 water samples were taken from 201 beaches, and in 2005, 628 water samples were taken from 177 beaches. The minimum inhibitory concentrations of the antimicrobial-resistant E coli isolates against a panel of 16 antimicrobials were determined using microbroth dilution. RESULTS: For 2004 and 2005, respectively, 28% and 38% of beaches sampled had at least one water sample contaminated by E coli resistant to one or more antimicrobials, and more than 10% of the resistant isolates were resistant to at least one antimicrobial of clinical importance for human medicine. The three antimicrobials with the highest frequency of resistance were tetracycline, ampicillin and sulfamethoxazole. DISCUSSION: The recreational waters of these beaches represent a potential source of antimicrobial-resistant bacteria for people engaging in water activities. Investigations relating the significance of these findings to public health should be pursued.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".