Weather, environmental conditions, and waterborne Giardia and Cryptosporidium in Iqaluit, Nunavut
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Indigenous communities in the Arctic often face unique drinking water quality challenges related to inadequate infrastructure and environmental contamination; however, limited research exists on waterborne parasites in these communities. This study examined Giardia and Cryptosporidium in untreated surface water used for drinking in Iqaluit, Canada. Water samples (n = 55) were collected weekly from June to September 2016 and tested for the presence of Giardia and Cryptosporidium using microscopy and polymerase chain reaction (PCR). Exact logistic regressions were used to examine associations between parasite presence and environmental exposure variables. Using microscopy, 20.0% of samples tested positive for Giardia (n = 11) and 1.8% of samples tested positive for Cryptosporidium (n = 1). Low water temperatures (1.1 to 6.7 °C) and low air temperatures (-0.1 to 4.5 °C) were significantly associated with an increased odds of parasite presence (p = 0.047, p = 0.041, respectively). These results suggest that surface water contamination with Giardia and Cryptosporidium may be lower in Iqaluit than in other Canadian regions; however, further research should examine the molecular characterization of waterborne parasites to evaluate the potential human health implications in Northern Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it