Bifidobacterial survival in surface water and implications for microbial source tracking
Bibliographic record
Abstract
Bifidobacteria are common in the intestines of humans and other animals. Sorbitol-fermenting Bifidobacteria (SFB) are associated with human faecal pollution. The ratio of total Bifidobacteria (TB) to SFB has been proposed to be a means for determining the source (human or animal) of faecal pollution. In this study, SFB were detected in all sewage samples (n = 39) and in 42% of samples of animal origin (n = 24): pig (5/6 positive), poultry (4/8), horse (1/4), and cow (0/6). The TB:SFB ratio was significantly higher in animal samples than in sewage samples (p < 0.01), with the exception of stored poultry manure, which had ratios (1.4-11) similar to the sewage samples (1-17). The lowest ratio in the other animal samples was 40 (pig). The TB:SFB ratio in sewage remained stable over time in surface water, and it may be a useful screening tool to determine the source of faecal pollution in surface water. Bifidobacteria died off in a log linear manner at 4 and 22 degrees C, with rates of disappearance of 0.16 and 0.58 log(days-1), respectively. Faecal coliforms (FC) disappeared more slowly (0.09 and 0.43 log(days-1), respectively). The FC:SFB ratio proved to be an inadequate tool for determining the age of sewage pollution.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".