The occurrence and sources of Campylobacter spp., Salmonellaenterica and Escherichia coli O157:H7 in the Salmon River, British Columbia, Canada
Bibliographic record
Abstract
In this study, we wished to assess the prevalence and determine the sources of three zoonotic bacterial pathogens (Salmonella, Campylobacter, and Escherichia coli O157:H7) in the Salmon River watershed in southwestern British Columbia. Surface water, sewage, and animal faecal samples were collected from the watershed. Selective bacterial culture and PCR techniques were used to isolate these three pathogens and indicator bacteria from these samples and characterize them. Campylobacter was the most prevalent pathogen in all samples, followed by Salmonella, and E. coli O157:H7. E. coli O157:H7 and Salmonella isolation rates from water, as well as faecal coliform densities correlated positively with precipitation, while Campylobacter isolation rates correlated negatively with precipitation. Analysis of DNA extracted from water samples for the presence of Bacteroides host-species markers, and comparisons of C. jejuni flaA-RFLP types and Salmonella serovars from faecal and water samples provided evidence that human sewage and specific domestic and wild animal species were sources of these pathogens; however, in most cases the source could not be determined or more than one source was possible. The frequent isolation of these zoonotic pathogens in the Salmon River highlights the risks to human health associated with intentional and unintentional consumption of untreated surface waters.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".