Drinking water in First Nation communities: occurrence of bacteria and identification of the resistome.
Bibliographic record
Abstract
Indigenous populations living on reserves in Canada today are still experiencing uneven access to drinking water services. Past studies of First Nation communities have observed microbiological contamination where no drinking water advisory was issued for fecal indicator bacteria (FIB) and detection of emerging contaminants: antibiotic resistance genes (ARG). The first study sought to observe fluctuations in the distribution system of traditional coliform indicators against antibiotic resistance genes as well as Campylobacter spp. quantification. Results found repeated detection of indicator bacteria from drinking water samples in homes with concrete cisterns in community B, as well as in community D up to 600 CFU/ 100 mL coliforms. Both Campylobacter coli and Campylobacter jejuni, diarrheal infection culprits, were also observed in instances without the previous or same-time detection of coliform, including at sampling sites like treated water from taps at the water treatment plant and piped homes. ARGs were more apparent in post-treated water from community B than from community D and in water treatment plant and piped samples. The second study sought to characterize ARGs through shotgun metagenomics to establish the resistome from water. Results determined pre-treated source water samples were characteristically distinct from post-treated cistern water from each community suggesting the presence of an alternative source of contamination for stored drinking water. Indigenous nations continue to experience water insecurity and these study results reinforce community concerns over water quality thus we aim to support change led within communities for strengthening the management of water distribution to homes.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".