Concentrations of organophosphate flame retardants in dust from cars, homes, and offices: An international comparison
Bibliographic record
Abstract
Concentrations of a number of organophosphate flame retardants (PFRs) were measured in floor dust collected from living rooms in Australia (n = 42), Canada (n = 14), Germany (n = 22), and Kazakhstan (n = 9); cars from Australia (n = 39) and Germany (n = 19); and offices from Germany (n = 25) and Kazahkstan (n = 8). PFR concentrations in these samples were compared with each other and with previously reported data for PFRs in dust from similar microenvironments in the UK. Our data reveal significant between-country differences in both absolute concentrations and the relative abundance of specific PFRs in each of the microenvironments studied. Most notably, concentrations of TCIPP in UK living room dust (median = 21 μg g−1) exceeded significantly (p < 0.05) those in all other countries studied here; a substantial number of car dust samples contained elevated concentrations of TDCIPP, and German samples generally contained lower levels of PFRs in all microenvironments studied. In addition, PFRs were determined in dust samples collected from living room couches in both Australia (n = 41) and the UK (n = 10). The elevated concentrations of TCIPP in UK living room dust are likely attributable to the favoured use of this PFR in UK couch foam. This is indicated by concentrations of TCIPP in UK couch dust (median = 610 μg g−1) exceeding significantly those in Australian couch dust (median = 2.9 μg g−1). Moreover, concentrations of TCIPP in UK couch dust originating from couches 15 years old or less, display a marked relationship with the age of the couch, with concentrations in such samples increasing significantly (p < 0.01) with couch age.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".