Spatial Patterns of Natural Polycyclic Aromatic Hydrocarbons in Sediment in the Lower Athabasca River
Bibliographic record
Abstract
The Athabasca Oil Sands is one of the four natural oil sands deposits in Northern Alberta, Canada, and are by far the largest oil sand deposit in North America, covering an area of 46,000 km2. Sediment samples were collected from the bed and bank of several tributaries that have naturally occurring exposures of oil sand material. Oil sand deposited along the lower Athabasca River, more than 100 km downstream of naturally occurring oil sand exposures, were also sampled. The levels of alkylated polycyclic aromatic hydrocarbons (PAHs) in samples collected from these various locations ranged from not detected to almost 50 ppm. Using dibenzothiophene/chrysene (C2/D2 vs. C3/D3) double ratio plots, it is possible to approximate the relative degree of degradation or weathering of the PAHs from these various sediment deposits along the lower Athabasca River and its tributaries. Similarly a plot of dibenzothiophene/phenanthrene (D2/P2 vs. D3/P3) indicate the possible origins of the oil. A combination of these plots, D3/P3 vs. D3/C3, was particularly useful in identifying weathering characteristics of different sources of the oil. Comparison of alkylated PAH distributions between the lower Athabasca River and the tributaries show slight differences consistent with different petrogenic sources and/or different weathering patterns.
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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 | 0.002 |
| Science and technology studies | 0.001 | 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".