Analysis of Settled Dust in Homes and Fungal Glucan in Air Particulate Collected during HEPA Vacuuming
Bibliographic record
Abstract
Six occupied single-family dwellings in Ottawa, Canada were subjected to weekly or bi-weekly professional cleaning using a HEPA filter-equipped vacuum cleaner and following a strict cleaning protocol based on floor area and type of floor. Sieved weights of dust were collected from each cleaning. Statistically significant reductions of fine dust loading occurred only after four sequential cleanings. As dust loading of the floor was reduced, exposure to dust mite allergens, endotoxins, and fungal glucans in dust decreased. During the first cleaning (when loadings were highest), airborne particles were collected using a MOUDI sampler (0.18—18 μm size fractions). The fungal polysaccharide β-(1, 3)-D-glucan was present in approximately equal proportions in each size fraction. This demonstrates that the majority of the fungal exposure was not to intact spores, but to fungal fragments much smaller than spores that have greater efficiency of deeper penetration into the lungs. This study also shows the importance of ensuring that cleaning interventions are effective before they can be related to health outcomes.
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.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".