Prevalence of indoor air pollutants from First Nation homes in North Central British Columbia, Canada
Bibliographic record
Abstract
Poor indoor air quality poses significant health risks. This study addresses the gap in knowledge regarding the prevalence of indoor air pollutants in remote and rural First Nation communities in north-central British Columbia, Canada. Dust samples from 75 homes were collected and analysed for house dust mites, pet allergens, mould antigens, and bacterial endotoxins. Indoor air quality parameters, including carbon monoxide, carbon dioxide, particulate matter, temperature, and humidity, were measured. A detailed questionnaire on household characteristics and potential pollutant sources was administered. Homes exhibited exposure to multiple pollutants, with wood stove smoke identified as a primary source. Felis domesticus (cat allergen) and Canis familiaris (dog allergen) were prevalent, with detectable levels in 64% and 60% of homes, respectively. Bacterial endotoxins were present in all households. One-third of homes exceeded recommended thresholds for 3 or more pollutants. This study provides critical insights into the prevalence and magnitude of indoor air pollutants, contributing to a broader initiative to characterise respiratory health in First Nations communities. While many homes in First Nations communities had acceptable air quality, one-third of homes exceeded thresholds for 3 or more pollutants. The results can guide ongoing community efforts to address housing concerns and advocate for increased federal funding.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".