The role of drinking water in the transmission of antimicrobial-resistant<i>E. coli</i>
Bibliographic record
Abstract
To determine whether drinking water contaminated with antimicrobial-resistant E. coli is associated with the carriage of resistant E. coli, selected households sending water samples to Ontario and Alberta laboratories in 2005-2006 were asked to participate in a cross-sectional study. Household members aged ≥12 years were asked to complete a questionnaire and to submit a rectal swab. In 878 individuals, 41% carried a resistant strain of E. coli and 28% carried a multidrug-resistant strain. The risk of carriage of resistant E. coli was 1·26 times higher for users of water contaminated with resistant E. coli. Other risk factors included international travel [prevalence ratio (PR) 1·33], having a child in nappies (PR 1·33), being male (PR 1·33), and frequent handling of raw red meats (PR 1·10). Protecting private water sources (e.g. by improving systems to test and treat them) may help slow the emergence of antimicrobial resistance in E. coli.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".