PAH sediment studies in Lake Athabasca and the Athabasca River ecosystem related to the Fort McMurray oil sands operations: sources and trends
Bibliographic record
Abstract
The oil sands operations in northern Alberta are among the most modem in the world, However, because the operations are extensive and lie on either side of the Athabasca River, there are concerns that they will adversely affect downstream environments such as the Athabasca River, its tributaries, the Peace-Athabasca deltas and Lake Athabasca, Research and monitoring programs are now investigating hydrocarbon sources, fate, and time trends in these aquatic ecosystems. Natural hydrocarbon sources (oil sands) are numerous along the Athabasca River and its tributaries. Petrogenic hydrocarbons also are abundant in downstream lakes. Lower molecular weight compounds such as naphthalene and fluorene tend to increase in concentration ffom upstream sources to downstream depositional areas, There is little or no evidence of temporal trends of increasing PAH concentrations in sediment cores collected in Lake Athabasca and the Athabasca delta lakes, suggesting no or minimal impact from the oil sands operations, Some PAHs exceed interim sediment quality guidelines and some bioassay studies have shown evidence of toxicity, particularly in the Athabasca delta. However, there is no evidence that this is associated with the oil sands industry, The RAMP monitoring program will continue to assess the potential impacts of the oil sands industry on river, tributary and delta ecosystems.
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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 | 0.000 |
| 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".