Comparative prevalence and diversity of <i>Campylobacter jejuni</i> strains in water and human beings over a 1-year period in southwestern Alberta, Canada
Bibliographic record
Abstract
Campylobacter jejuni was isolated from diarrheic people, river water (Oldman River watershed), wastewater, and drinking water over a 1-year period in southwestern Alberta (2008–2009). High rates of campylobacteriosis were observed during the study period (≥115 cases/100 K). Infections occurred throughout the year, with peaks in late summer and early autumn. Most infections occurred in people living in Lethbridge. Campylobacter jejuni was not isolated from municipal drinking water. In contrast, the bacterium was isolated from untreated and treated wastewater and river water (all sites). There were no correlations between C. jejuni recovery/detection from water and river flow rates, water turbidity, or fecal coliforms. Campylobacter jejuni recovery from water did not correspond to the peak periods of campylobacteriosis. The bacterium was most commonly isolated downstream of wastewater outfalls; waterfowl congregated at these sites, particularly during the winter months. A comparison of C. jejuni isolates from people and water revealed that most subtypes in water did not correspond to subtypes recovered from diarrheic people and were linked to waterfowl and other non-human animal sources. We conclude that waterborne C. jejuni did not contribute significantly to the high rates of campylobacteriosis observed in diarrheic people during the study period.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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".