Polycyclic Aromatic Hydrocarbons Increase in Athabasca River Delta Sediment: Temporal Trends and Environmental Correlates
Bibliographic record
Abstract
The Athabasca River in Alberta, Canada, flows north through an area undergoing extensive bitumen resource extraction and processing before discharging its water and sediments into the Athabasca Delta and Lake Athabasca. Polycyclic aromatic hydrocarbons (PAHs) have been identified as an environmental concern in the region. We analyzed environmental data collected by the Regional Aquatics Monitoring Program and government agencies to determine whether temporal trends exist in the concentration of sediment PAHs in the Athabasca River Delta. We then determined what environmental factors related to the trends in sediment PAH concentrations. Total PAH concentrations in the sediment of the Athabasca River Delta increased between 1999 and 2009 at a rate of 0.05 mg/kg/yr ± 0.02 s.e. Annual bitumen production and mined sand volume, extent of landscape disturbance, and particulate emissions were correlated with sediment PAH concentrations as were total organic carbon in sediment and discharge of the Clearwater River, a major tributary of the Athabasca River. Within four tributaries of the Athabasca River, only the Clearwater River showed a significant correlation between discharge and sediment PAH concentration at their river mouths. Carefully designed studies are required to further investigate which factors best explain variability in sediment PAH concentrations.
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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 | 0.000 | 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".