Tracking Host Sources of <i>Cryptosporidium</i> spp. in Raw Water for Improved Health Risk Assessment
Bibliographic record
Abstract
Recent molecular evidence suggests that different species and/or genotypes of Cryptosporidium display strong host specificity, altering our perceptions regarding the zoonotic potential of this parasite. Molecular forensic profiling of the small-subunit rRNA gene from oocysts enumerated on microscope slides by U.S. Environmental Protection Agency method 1623 was used to identify the range and prevalence of Cryptosporidium species and genotypes in the South Nation watershed in Ontario, Canada. Fourteen sites within the watershed were monitored weekly for 10 weeks to assess the occurrence, molecular composition, and host sources of Cryptosporidium parasites impacting water within the region. Cryptosporidium andersoni, Cryptosporidium muskrat genotype II, Cryptosporidium cervine genotype, C. baileyi, C. parvum, Cryptosporidium muskrat genotype I, the Cryptosporidium fox genotype, genotype W1, and genotype W12 were detected in the watershed. The molecular composition of the Cryptosporidium parasites, supported by general land use analysis, indicated that mature cattle were likely the main source of contamination of the watershed. Deer, muskrats, voles, birds, and other wildlife species, in addition to sewage (human or agricultural) may also potentially impact water quality within the study area. Source water protection studies that use land use analysis with molecular genotyping of Cryptosporidium parasites may provide a more robust source-tracking tool to characterize fecal impacts in a watershed. Moreover, the information is vital for assessing environmental and human health risks posed by water contaminated with zoonotic and/or anthroponotic forms of Cryptosporidium.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".