Indoor and Outdoor Particulate Matter Exposure of Rural Interior Alaska Residents
Bibliographic record
Abstract
To assess the exposure of residents in rural communities in the Yukon Flats to particulate matter of 2.5 μm or less in diameter (PM2.5), both indoor and outdoor concentration observations were carried out from March to September 2019 in Ft. Yukon, Alaska. Indoor concentrations were measured at 0.61 m (breathing level during sleeping) in homes and at 1.52 m heights (breathing level of standing adult) in homes and office/commercial buildings. Air quality was better at both heights in cabins than frame homes both during times with and without surface-based inversions. In frame houses, concentrations were higher at 0.61 m than 1.52 m, while the opposite is true typically for cabins. Differences between shoulder season and summer indoor concentrations in residences were related to changes in heating, subsistence lifestyle and mosquito repellents. In summer, office and commercial buildings, air quality decreased due to increased indoor emissions related to increased use of equipment and mosquito pics as well as more merchandise. During summer indoor concentrations reached unhealthy for sensitive groups to hazardous conditions for extended times that even exceeded the high outdoor concentrations. Due to nearby wildfires, July mean outdoor concentrations were 55.3 μg·m-3 which exceeds the 24-h US National Ambient Air Quality Standard of 35 μg·m-3. Indoor and outdoor concentrations correlated the strongest with each other for office/commercial buildings, followed by frame houses and cabins. Office/commercial buildings with temperature monitors had one to two orders of magnitude lower concentrations than those without.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".