Investigating the impact of filters on long-term particle concentration measurements in residences (RP-1649)
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
Filters in heating, ventilation, and air-conditioning (HVAC) systems are the most prevalent air cleaning method in residential environments in North America. This study evaluated the long-term impact of residential filtration systems on indoor particle concentrations by examining concentration measurements from low-cost monitors over one year in twenty homes in Toronto, Ontario, Canada. These concentration results suggested that in general, indoor concentration had a similar seasonal trend as the ambient concentration, and indoor activities (e.g., cooking) elevated indoor particle levels for 40-50% of the time. Further, the impacts of electret filters were examined using a non-electret filter with a minimum efficiency reporting value (MERV) of 8 as the reference point at each home. The mean effectiveness of the filters (MERV 8E = −4.19%, MERV 11E = −0.51%, and MERV 14E = 14.5%) were lower than values found in the literature, most likely due to lower HVAC system runtime in our sample of homes (median = 9.6%). Overall, this filter effectiveness analysis reveals that the real-life filter performance was strongly influenced by system and house characteristics (e.g., system runtime, in-situ efficiency, air change rate, and particle source strength), and thus can be different from modeling and laboratory test results.
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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 | 0.001 | 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 | 0.003 |
| 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