Where's the pump? Associating sporadic enteric disease with drinking water using a geographic information system, in British Columbia, Canada, 1996–2005
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We investigated whether risk of sporadic enteric disease differs by drinking water source and type using surveillance data and a geographic information system. We performed a cross-sectional analysis, at the individual level, that compared reported cases of enteric disease with drinking water source (surface or ground water) and type (municipal or private). We mapped 814 cases of campylobacteriosis, cryptosporidiosis, giardiasis, salmonellosis and verotoxigenic Escherichia coli infection, in a region of British Columbia, Canada, from 1996 to 2005, and determined the water source and type for each case's residence. Over the 10-year period, the risk of disease was 5.2 times higher for individuals living on land parcels serviced by private wells and 2.3 times higher for individuals living on land parcels serviced by the municipal surface/ground water mixed system, than the municipal ground water system. Rates of sporadic enteric disease potentially differ by drinking water source and type. Geographic information system technology and surveillance data are accessible to local public health authorities and used together are an efficient and affordable way to assess the role of drinking water in sporadic enteric disease.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it