Multiyear Measurements of Flame Retardants and Organochlorine Pesticides in Air in Canada’s Western Sub-Arctic
Bibliographic record
Abstract
Fourteen polybrominated diphenyl ethers (PBDEs), 14 non-BDE flame retardants (FRs), and 25 organochlorine pesticides (OCPs) were analyzed in air samples collected at Little Fox Lake (LFL) in Canada's Yukon Territory from August 2011 to December 2014. LFL is a long-term monitoring station operated under the Northern Contaminants Program (NCP) and one of only a few stations that contribute to the assessment of air pollution levels and pathways to the sub-Arctic region. BDE-47 was the most abundant congener among the 14 PBDEs, followed by BDE-99. Non-BDE FRs pentabromotoluene (PBT) and dechlorane plus (DP) were detected in all the samples. Dechlorane 602, 2,3-dibromopropyl-2,4,6-tribromophenyl ether (DPTE), hexabromobenzene (HBB), and 2-ethylhexyl-2,3,4,5-tetrabromobenzoate (EH-TBB) were also detected in >75% of all samples. PBDEs have shown a decreasing tendency as of 2013, which may reflect the phase-out of penta- and octa-BDE mixtures has led to significant decline in the atmosphere. The highest concentrations of OCPs were observed for hexachlorobenzene (HCB), with a median concentration of 61 pg/m(3), followed by α-hexachlorocyclohexane (α-HCH) and α-endosulfan. Potential source contribution function (PSCF) highlights Northern Canada, Pacific, and East Asia as potential sources in warm seasons; whereas in cold seasons, the chemicals mainly came from the Pacific Rim.
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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) | 0.000 | 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".