The dynamics of faecal indicator organisms in a temperate river during storm conditions
Bibliographic record
Abstract
Greater incidence of storm events, which can lead to greater contamination of surface waters by human and animal faeces, are a predicted feature of climate change in parts of Europe and elsewhere. The aim of this study was to combine the use of a novel quantitative microbial source tracking (QMST) method with established water quality monitoring procedures during an intense summer storm event in a rural UK river catchment, to establish dominant sources of faecal pollution. One-litre grab samples of river water were collected every 12 h for a period of seven days from three sampling sites on the Bevern Stream (a tributary of the Sussex Ouse). All samples were tested for a range of chemophysical and bacteriological parameters, and also for phage-lysis of a human specific strain of Bacteroides spp. GB-124. Presumptive levels of Escherichia coli and intestinal enterococci were statistically significantly (p-value < 0.05) higher during the storm event, compared with dry weather conditions. Low recorded levels of phages of Bacteroides GB-124 during the storm event, compared with dry weather conditions, support the hypothesis that the predominant sources of faecal material in the river during the storm event were non-human. Using traditional faecal indicator bacteria and a QMST marker during storm events may improve human health protection protocols.
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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 | 0.000 |
| 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".