Exploring the Long-Term Human Exposure to Short-, Medium-, and Long-Chain Chlorinated Paraffins under Variant Environmental Release Trends and Patterns
Bibliographic record
Abstract
Releases of chlorinated paraffins (CPs) have led to long-term human exposure globally. Differences in CP use patterns (indoors vs outdoors) and temporal release trends in different regions may be reflected in differences in the extent and pathways of long-term exposure to CPs between human populations. We used the dynamic mechanistic model PROTEX to simulate releases and environmental fates of CPs in China, Canada, and Europe from 1930 to 2020 and contrast the resultant exposures for different birth cohorts. Predicted environmental and human body concentrations agree with measurements from the three regions. Far-field exposure pathways dominate for all cohorts even in China where CP indoor use is high. Longitudinal exposure trends differ between generations and regions due to the divergent release trends. Perinatal exposure causes high body concentrations in infants and children born in years with peak releases. Due to human elimination half-lives that are short relative to the period of release, cross-sectional concentration-age trends have similar shapes regardless of release trend and sampling time. These results imply that whereas use patterns and release trends add to the influence of physicochemical properties on relative exposure pathway importance and cross-sectional concentration-age trends, the release trends are the main factors shaping longitudinal exposure trends.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".