Microbiological Contamination of Urban Groundwater in the Brazilian Western Amazon
Bibliographic record
Abstract
Groundwater is heavily exploited for a variety of uses. Depending on their structure, the wells from which water is extracted can act as an entry point/gateway for a variety of microbiological contaminants, which can cause numerous adverse health effects. This study aimed to identify the microorganisms present in the groundwater in the Western Amazonian city of Porto Velho, using a methodology that can be deployed in other city centers. We collected 74 water samples from both dug and drilled wells in March, August and November 2018. Total coliforms were detected in 96% of dug wells and 74% of drilled wells. Thermotolerant coliforms were found in 90% of dug wells and 61% of drilled wells. Biochemical identification indicated 15 genera of bacteria. The genera Escherichia, Enterobacter, Cronobacter and Citrobacter had the highest prevalence. The genera Pseudomonas and Enterococcus were also detected. Thermotolerant coliforms showed higher values when the water flow was higher. Our results indicate high fecal contamination and higher susceptibility to contaminants in shallow wells compared to deep wells. These findings reflect the precariousness of WASH (water, sanitation and hygiene) services and the importance of effective actions to combat groundwater degradation, improve the quality of the environment, and protect public health.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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 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".