Routes of human exposure to per- and polyfluorinated compounds (PFCs) in Winnipeg homes
Bibliographic record
Abstract
Per and polyfluorinated compounds (PFCs) include a large group of chemicals which are known to be toxic, bioaccumulative and resistant to hydrolysis, photolysis, microbial degradation and metabolism. However, human exposure pathways and toxic effects to humans are still widely unknown and more data is needed over time. The concentrations of 7 PFCs were measured in indoor air from homes in Winnipeg, Manitoba using gas chromatography-mass spectrometry. 16 PFCs were measured in house dust from Winnipeg, Manitoba using on-line solid phase extraction coupled with liquid chromatography mass spectrometry. For commonly detected PFCs in indoor air and dust, concentrations were found at pg/m3 and ng/g levels, respectively, similar to that observed in other recent studies. Appropriate statistical tests and principal component analysis were used to evaluate possible associations between PFC concentrations and home characteristics. PFCs in indoor air and dust were associated with each other and home characteristics but not with indoor ambient temperature nor type of room (child room or the most used room). Furthermore PFCs did not show significant association with infant wheezing. None of the neutral PFCs in indoor air showed an association with seasonal temperature variation, except 8:2 FTOH and MeFOSE that had significantly higher concentrations in winter than summer.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".