Assessment of Giardia and Cryptosporidium spp. as a Microbial Source Tracking Tool for Surface Water: Application in a Mixed-Use Watershed
Bibliographic record
Abstract
Knowledge of host specificity, combined with genomic sequencing of Giardia and Cryptosporidium spp., has demonstrated a microbial source tracking (MST) utility for these common waterborne microbes. To explore the source attribution potential of these pathogens, water samples were collected in a mixed rural-urban watershed in the Township of Langley, in southwestern British Columbia (BC), Canada, over a 2-year period. Cryptosporidium was detected in 63% of surface water samples at concentrations ranging from no positive detection (NPD) to 20,600 oocysts per 100 liters. Giardia was detected in 86% of surface water samples at concentrations ranging from NPD to 3,800 cysts per 100 liters of water. Sequencing at the 18S rRNA locus revealed that 50% of Cryptosporidium samples and 98% of Giardia samples contained species/genotypes (Cryptosporidium) or assemblages (Giardia) that are capable of infecting humans, based on current knowledge of host specificity and taxonomy. Cryptosporidium genotyping data were more promising for source tracking potential, due to the greater number of host-adapted (i.e., narrow-host-range) species/genotypes compared to Giardia, since 98% of Giardia isolates were zoonotic and the potential host could not be predicted. This report highlights the benefits of parasite genomic sequencing to complement Method 1623 (U.S. Environmental Protection Agency) and shows that Cryptosporidium subtyping for MST purposes is superior to the use of Giardia subtyping, based on better detection limits for Cryptosporidium-positive samples than for Giardia-positive samples and on greater host specificity among Cryptosporidium species. These additional tools could be used for risk assessment in public health and watershed management decisions.
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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 | 0.000 | 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".