Carcinogenic metal(loid)s in house dust compared to soil: Concentrations and gastric bioaccessibility
Bibliographic record
Abstract
As a sink and a source of chemicals, house dust represents a relevant medium to assess indoor exposure to metal(loid)s via incidental ingestion or inhalation. However, nationally representative indoor data are scarce. Results from the Canadian House Dust Study (CHDS 2007-2010; n = 1025) provide nationally representative mean, median and 95th percentile concentrations for 38 elements in typical urban house dust, along with their gastric bioaccessibility. Total concentrations (median/95th percentile) of carcinogenic metal(loid)s in Canadian house dust (μg g-1) are as follows: As (9.0/40), Be (0.4/0.9), Cd (3.5/17), Co (5.6/19), Cr (99/214), Ni (62/322) and Pb (100/760). Total As and Pb concentrations in house dust exceed residential soil guidelines for the protection of human health in about one-third of Canadian homes. Percent bioaccessibilities (median) are: Cd (65%) > Pb (63%) > Be ∼Ni (36%) > Co (35%) > As (20%) > Cr (15%). Lead, Cd and Co concentrations are significantly greater in older houses (< 1976). Data from two pilot studies (n = 66+51) further demonstrate the distinct geochemistry of house dust compared to soils, notably enrichment of carcinogenic metal(loid)s and their increased bioaccessibility. These results provide essential baseline values to refine risk assessment and inform on health risk at contaminated sites.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".