The occurrence of Campylobacter in river water and waterfowl within a watershed in southern Ontario, Canada
Bibliographic record
Abstract
AIMS: Quantitative PCR and a culture method were used to investigate Campylobacter occurrence over 3 years in a watershed located in southern Ontario, Canada that is used as a source of drinking water. METHODS AND RESULTS: Direct DNA extraction from river water followed by quantitative PCR analysis detected thermophilic campylobacters at low concentrations (<130 cells 100 ml(-1) ) in 57-79% of samples taken from five locations. By comparison, a culture-based method detected Campylobacter in 0-23% of samples. Water quality parameters such as total Escherichia coli were not highly correlated with Campylobacter levels, although higher pathogen concentrations were observed at colder water temperatures (<10°C). Strains isolated from river water were primarily nalidixic acid-susceptible Campylobacter lari, and selected isolates were identified as Campylobacter lari ssp. concheus. Campylobacter from wild birds (seagulls, ducks and geese) were detected at a similar rate using PCR (32%) and culture-based (29%) methods, and although Campylobacter jejuni was isolated most frequently, C. lari ssp. concheus was also detected. CONCLUSIONS: Campylobacter were frequently detected at low concentrations in the watershed. Higher prevalence rates using quantitative PCR was likely because of the formation of viable but nonculturable cells and low recovery of the culture method. In addition to animal and human waste, waterfowl can be an important contributor of Campylobacter in the environment. SIGNIFICANCE AND IMPACT OF THE STUDY: Results of this study show that Campylobacter in surface water can be an important vector for human disease transmission and that method selection is important in determining pathogen occurrence in a water environment.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".