The association between campylobacteriosis, agriculture and drinking water: a case-case study in a region of British Columbia, Canada, 2005–2009
Bibliographic record
Abstract
We studied the association between drinking water, agriculture and sporadic human campylobacteriosis in one region of British Columbia (BC), Canada. We compared 2992 cases of campylobacteriosis to 4816 cases of other reportable enteric diseases in 2005-2009 using multivariate regression. Cases were geocoded and assigned drinking water source, rural/urban environment and socioeconomic status (SES) according to the location of their residence using geographical information systems analysis methods. The odds of campylobacteriosis compared to enteric disease controls were higher for individuals serviced by private wells than municipal surface water systems (odds ratio 1·4, 95% confidence interval 1·1-1·8). In rural settings, the odds of campylobacteriosis were higher in November (P = 0·014). The odds of campylobacteriosis were higher in individuals aged ⩾15 years, especially in those with higher SES. In this region of BC, campylobacteriosis risk, compared to other enteric diseases, seems to be mediated by vulnerable drinking water sources and rural factors. Consideration should be given to further support well-water users and to further study the microbiological impact of agriculture on water.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".