Predictors of indoor BTEX concentrations in Canadian residences.
Bibliographic record
Abstract
BACKGROUND: Benzene, toluene, ethylbenzene and m-, p-xylenesand o-xylene (BTEX) are a group of volatile organic compounds that originate from similar sources. Given the potentially negative health implications of BTEX exposure and their prevalence in residential indoor air, it is important to understand typical residential concentrations and identify predictors. DATA AND METHODS: The 2009 to 2011 Canadian Health Measures Survey included an indoor air component. Questionnaires were administered, and respondents were asked to deploy an air sampler in their home for 7 consecutive days. This analysis is based on BTEX data from 5,191 respondents. Mean BTEX concentrations were examined overall, and by dwelling type and garage configuration. Stepwise regression models were used to examine potential sources of BTEX components. RESULTS: Means were 1.95 μg/m³ (benzene), 19.17 μg/m³ (toluene), 4.09 μg/m³ (ethylbenzene), 14.42 μg/m³ (m-, p-xylenes), and 4.16 μg/m³ (o-xylene). Significant predictors of the presence of BTEX included a garage on the property, regular smoking in the home, renovations in the past month, number of occupants, use of paint remover, and use of fragrance. INTERPRETATION: Results of this nationally representative study found that BTEX concentrations are relatively low among Canadian residences, and identified several different indoor sources.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".