Ecological Risk Assessment of Oil Spills in Ice-Covered Waters: A Surface Slick Model Coupled with a Food-Web Bioaccumulation Model
Bibliographic record
Abstract
The limited knowledge on oil-ice interactions and on the ecological outcomes of oil spills in the Arctic represent sources of uncertainties for shipping and oil and gas activities in polar regions. The present work aims at the definition of the ecological risk posed by oil spills in the Arctic by the integration of an improved surface slick model to a fugacity-based food-web bioaccumulation model for icy waters. The model's outcomes are the representation of transport and weathering processes and the concentrations of a toxic component of oil, namely naphthalene, in the environmental media as a function of ice conditions. Given those concentrations, the associated ecological risk is defined in terms of the bioconcentration factor (BCF). Overall, the model predicted low bioaccumulation and biomagnification potential for naphthalene to a hypothetical Arctic food web, regardless of the ice concentration. Integr Environ Assess Manag 2020;16:729-744. © 2020 SETAC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".