Quantitative PCR assay of sewage-associated<i>Bacteroides</i>markers to assess sewage pollution in an urban lake in Dhaka, Bangladesh
Bibliographic record
Abstract
This paper aimed to assess the magnitude of sewage pollution in an urban lake in Dhaka, Bangladesh, by using quantitative PCR of sewage-associated Bacteroides HF183 markers. PCR was also used for the quantitative detection of ruminant wastewater-associated CF128 markers along with the enumeration of traditional fecal indicator bacteria, namely enterococci. The number of enterococci in lake water samples ranged from 1.1 × 10⁴ to 1.9 × 10⁵ colony-forming units/100 mL water. From the 20 water samples tested, 14 (70%) and 7 (35%) were PCR positive for HF183 and CF128 markers, respectively. The numbers of HF183 and CF128 markers in lake water samples were 3.9 × 10⁴ to 6.3 × 10⁷ and 9.3 × 10³ to 6.3 × 10⁵ genomic units/100 mL water, respectively. The high numbers of enterococci and HF183 markers are indicative of sewage pollution and potential health risks to those who use the lake water for nonpotable purposes such as bathing and washing clothes. This is the first study that investigated the presence of microbial source tracking markers in Dhaka, Bangladesh, where diarrhoeal disease is one of the major causes of childhood mortality. The molecular assay used in this study can provide valuable information on the extent of sewage pollution, thus facilitating the development of robust strategies to minimize potential health risks.
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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 | 0.002 | 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) | 0.001 | 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 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".