Deposition Mapping of Polycyclic Aromatic Compounds in the Oil Sands Region of Alberta, Canada and Linkages to Ecosystem Impacts
Bibliographic record
Abstract
This study produced gridded deposition estimates of polycyclic aromatic compounds (PACs), including 17 polycyclic aromatic hydrocarbons (PAHs), 21 alkylated PAHs (alk-PAHs), and 5 dibenzothiophenes (DBTs), over the oil sands region of Alberta, Canada and surrounding communities. Gridded annual total deposition of PACs in 2011 ranged from 55 to 175 000 μg m –2 yr –1 and the mean and median fluxes were 1700 and 760 μg m –2 yr –1, respectively. The domain-wide mean dry and wet deposition were 600 and 1100 μg m –2 yr –1 . PAHs, alk-PAHs and DBTs contributed 19%, 74%, and 7% to the total dry deposition, and 42%, 49%, and 9% to the total wet deposition. Dominant chemical species contributing to total deposition were naphthalene, retene and phenanthrene for PAHs and C2-benz[a]anthracene/triphenylene/chrysene, C2-fluoranthene/pyrene and C2-fluorene for alk-PAHs. The highest PAC deposition was found over the surface mineable area, which received 9 times the deposition flux of outlying areas. Additional deposition hotspots were also observed south of the surface mineable area notably over in situ bitumen production sites. The deposition of alk-PAHs impacted a more extensive area than that of PAHs or DBTs. This result suggests that atmospheric deposition is a key process in wildlife exposure to PACs across the region.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 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".