Prevalence of Giardia and Cryptosporidium and characterization of Cryptosporidium spp. isolated from wildlife, human, and agricultural sources in the North Saskatchewan River Basin in Alberta, Canada
Bibliographic record
Abstract
The environmental distribution of Giardia spp. and Cryptosporidium spp. is dependent upon human, agricultural, and wildlife sources. The significance of each source with regard to the presence of parasites in the environment is unknown. This 2-year study examined parasite prevalence in human sewage influent, wildlife, and agricultural sources associated with the North Saskatchewan River Basin in Alberta, Canada. Fecal samples were collected from cow-calf, dairy, and hog operations in the watershed area. Sewage-treatment facilities were sampled bimonthly during the 2-year study, and wildlife scat was collected at locations along tributaries of the North Saskatchewan River. All samples were analyzed for the presence of Giardia and Cryptosporidium, using sucrose-gradient separation followed by immunofluorescent microscopy. Giardia and Cryptosporidium were detected in all three sources. The lowest prevalence of both Giardia (3.28%) and Cryptosporidium (0.94%) was found in wildlife, with 6 of 19 species testing positive. Sewage influent had the highest prevalence of Giardia (48.80%) and Cryptosporidium parvum-like oocysts (5.42%); however, the concentration of both parasites was minimal compared with the concentration detected in cattle feces. Cow-calf sources contained the highest concentration of Giardia (mean 5800/g feces, P < 0.01), and dairy sources contained the highest concentration of C. parvum-like oocysts (mean 295/g feces, P < 0.01). Although prevalence and concentration are higher in cattle feces than in sewage, the Giardia and Cryptosporidium in animal manure do not have direct access to water draining into the North Saskatchewan River. PCR-based characterization of rDNA from isolates of Cryptosporidium collected from Alberta human, pig, calf, mature steer, dog, cat, and beaver hosts revealed distinct genetic differences that may reflect host specificity.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".