Year-round monitoring of three water sources in Québec, Canada, reveals site-specific differences in conditions for <i>Cryptosporidium</i> and <i>Giardia</i> contamination
Bibliographic record
Abstract
Cryptosporidium and Giardia are protozoan parasites responsible for gastrointestinal illnesses in humans and in animal species. The main way these parasites are transmitted is by ingestion of their (oo)cysts in drinking water. Monitoring (oo)cysts in water sources is beneficial to evaluate the quality of raw water supplying treatment plants. Currently, the only standardized protocol to enumerate these parasites from water samples is United States Environmental Protection Agency (USEPA) Method 1623.1. With this method, we monitored three major water sources in Quebec over a year to assess temporal and geographical variations of these parasite (oo)cysts. These three water sources have independent watersheds despite being in the same region. We found a general pattern for Giardia, with high concentrations of cysts during cold and transition periods, and significantly lower concentrations during the warm period. Cryptosporidium’s concentration was more variable throughout the year. Statistical correlations (Pearson’s correlation coefficients) were established between the concentration of each parasite and various environmental parameters. The three study sites each showed unique factors correlating with the presence of both protozoa, supporting the idea that each water source must be seen as a unique entity with its own particular characteristics and therefore, must be monitored independently. Although some environmental parameters could be interesting proxies to the parasitic load, no parameter was strongly correlated throughout the whole sampling year and none of the parameters could be used as a single proxy for all three studies sources.
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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 | 0.001 | 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".