Modelling the Effects of Chemical Dispersant on the Fate of Spilled Oil: Case Study of a Hypothetical Spill near Saint John, NB
Bibliographic record
Abstract
The proposed Energy East pipeline project has raised concerns about potential oil spills in Saint John, New Brunswick, due to increased tanker traffic.While environmental conditions such as strong tide and current could pose challenges for using mechanical recovery methods if a spill occurs in the area, chemical dispersant could be an alternative oil spill countermeasure.However, the application of chemical dispersant in shallow water and costal zones remains an issue of debate.To study if chemical dispersant could be effective for potential oil spills in Saint John, a 3-dimensional model was used to simulate the transport of oil following a hypothetical release of 1000 m 3 Arabian Light crude under winter conditions.A stochastic approach was used to take into account the uncertainties of environmental inputs.The results show a significant reduction of oil ashore, and enhanced biodegradation with dispersant application, but these effects were accompanied by an increase of oil in sediment and water column, which is a concern.While the results are only conclusive for the selected scenarios of winter release, the method could be extended to other months and seasons of the year to support more detailed net environmental benefit analysis regarding dispersant application.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".