Determinants of the geographical distribution of endemic giardiasis in Ontario, Canada: a spatial modelling approach
Bibliographic record
Abstract
Giardiasis surveillance data as well as drinking water, socioeconomic and land-use data were used in spatial regression models to investigate determinants of the geographic distribution of endemic giardiasis in southern Ontario. Higher giardiasis rates were observed in areas using surface water [rate ratio (RR) 2.36, 95 % CI 1.38-4.05] and in rural areas (RR 1.79, 95 % CI 1.32-2.37). Lower rates were observed in areas using filtered water (RR 0.55, 95 % CI 0.42-0.94) and in those with high median income (RR 0.62, 95 % CI 0.42-0.92). Chlorination of drinking water, cattle density and intensity of manure application on farmland were not significant determinants. The study shows that waterborne transmission plays an important role in giardiasis distribution in southern Ontario and that well-collected routine surveillance data could be useful for investigation of disease determinants and identification of high-risk communities. This information is useful in guiding decisions on control strategies.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".