In‐situ effectiveness of residential HVAC filters
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
In this study, we explore different filter and contextual characteristics that influence effectiveness of high-efficiency filters in 21 residences in Toronto, Canada. The in situ effectiveness was assessed with decay tests at the beginning and the end of filter life with four different filters (MERV 8-14 from ASHRAE Standard 52.2) installed in operational HVAC systems, compared with either the system off or with no filter installed. There was considerable difference between median PM2.5 effectiveness of the non-electret filters when compared to electret filters (16% vs. 36%) of the same nominal efficiency (MERV 8). However, median PM2.5 effectiveness of electret filters only slightly improved (between 5% and 9% absolute increase) as MERV increased from 8 to 14. There was more variation in filter effectiveness between the same filter in different homes than there was between different filters in the same home. Variations in filter performance arose because home-specific particle loss rates (eg, ventilation rate) vary greatly in different buildings. The higher the loss rates due to non-filter factors, the lower the effectiveness of a filter. Given the relatively large variation in effectiveness for a given filter over time and in different homes, increasing system runtime may be a productive way to improve filter performance in many homes.
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