Laboratory method for aerosolization and collection of PM <sub>10</sub> from settled house dust
Bibliographic record
Abstract
Inhalation of airborne particulate matter with a median aerodynamic diameter less than 10 µm (PM10) can have adverse health effects. Settled house dust is a relevant medium to assess residential chemical exposure through ingestion and inhalation. Understanding the chemical composition of house dust’s PM10 is needed for human health risk assessment. However, separation and collection of PM10 from house dust, in sufficient amount for subsequent characterization, represents a technical challenge. A method to resuspend settled house dust to collect its PM10 fraction was developed. House dust samples (<80 µm) were resuspended using a vortex which generated airborne particles that were entrained in a cyclone where particles larger than 10 µm were removed. PM10 were collected simultaneously on two PTFE filters (0.45 µm) located at the cyclone′s output. Scanning electron microscopy analysis was used as a qualitative complementary technique to visually assess the collected particles and the particle size segregation efficiency. The amount of collected PM10 ranged from 2.19 to 143.14 mg and was impacted by the operating flow rate, the ambient conditions (temperature and relative humidity), and to a lesser extent by the dust characteristic (stickiness). The method yielded consistent PM10 recoveries within samples (coefficients of variation of triplicates ≤17% (n = 7); except for three samples with variability up to 57%). The observed variability could be explained by the heterogeneous nature of house dust. This methodology will help advance chemical characterization of PM10 to refine risk assessment of residential chemical exposure.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".