Oil sands and the marine environment: current knowledge and future challenges
Bibliographic record
Abstract
The environmental consequences of bitumen extraction from oil sands deposits are at the center of North American natural resource and energy policy debate, yet impacts on ocean environments have received little attention. Using a quantitative framework, we identify knowledge gaps and research needs related to the effects of oil sands development on marine biota. Fifteen sources of stress and disturbance – varying greatly in spatial and temporal scale – are generated via two pathways: (1) the coastal storage and oceanic transport of bitumen products, and (2) the contribution of industry‐derived greenhouse gases to climate change in the ocean. Of highest research priority are the fate, behavior, and biological effects of bitumen in the ocean. By contrast, climate‐change impacts are scientifically well established but not considered in key regulatory processes. Most stressors co‐occur and are generated by other industries, yet cumulative effects are so far unaccounted for in decision making associated with new projects. Our synthesis highlights priority research needed to inform future energy development decisions, and opportunities for policy processes to acknowledge the full scope of potential and realized environmental consequences.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".