Human biomonitoring of dioxins, furans, and non-ortho dioxin-like polychlorinated biphenyls (PCBs) in blood plasma from Old Crow, Yukon, Canada (2019)
Bibliographic record
Abstract
Dioxins, furans, and dioxin-like polychlorinated biphenyls (PCBs) are a group of persistent and toxic chemicals that are known to have human health effects at low levels. These chemicals have been produced for commercial use (PCBs) or unintentionally as by-products of industry or natural processes (PCBs, dioxins, and furans). Additionally, dioxin-like PCBs were formerly used in electrical applications before being banned internationally (2004). These chemicals are widely dispersed in the environment as they can contaminate air and travel hundreds to thousands of kilometers before depositing on land or water, thereafter, potentially entering food chains. Community concerns surrounding the safety of traditional foods prompted a human biomonitoring project in Old Crow, Yukon Territory (YT), Canada (2019). Through collaborative community engagement, dioxins and like compounds were identified as a priority for exposure assessment from biobanked samples. In 2022, biobanked plasma samples (n = 54) collected in Old Crow were used to measure exposures to seven dioxins, ten furans, and four dioxin-like PCBs. 1,2,3,6,7,8-HxCDD, 1,2,3,7,8,9-HxCDD, 1,2,3,4,6,7,8-HpCDD, OCDD, 2,3,4,7,8-PeCDF, 1,2,3,6,7,8-HxCDF, PCB 126, and PCB 169 were detected in at least 50 % of samples. Among these analytes, the only congener at elevated levels was PCB 169, which was approximately ∼2-fold higher than the general population of Canada. No significant sex-based or body mass index (BMI) differences in biomarker concentrations were observed. Generally, the concentrations of the detected congeners increased with age, except for 1,2,3,4,6,7,8-HpCDD. For the first time, this research measures dioxin and like-compound exposures in Old Crow, advancing the information available on chemical exposures in the Arctic. Further research could be directed towards the investigation of PCB 169 exposure sources and temporal monitoring of exposures and determinants.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 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".