Approaches to Nontank Vessel Contingency Planning1
Bibliographic record
Abstract
ABSTRACT Tank vessels that carry oil as cargo are subject to a number of international, national, and local regulations requiring that the vessel owners plan for and be prepared to respond to oil spills. By comparison, nontank vessels such as freighters, passenger ships, and fishing vessels typically have not been subject to the same level of oil spill prevention and response requirements. However, a number of recent, high-profile nontank vessel oil spills have heightened public awareness of the oil spill risk posed by nontank vessels. In response to such events, several US states have implemented regulations requiring nontank vessels to prepare oil spill contingency plans similar to those required for tankers and tank barges. This paper considers several different approaches to oil spill contingency planning for nontank vessels, focusing on the Pacific coast of the United States and Canada. The authors compare the requirements in place in Alaska, California, Washington, Oregon and British Columbia, and make recommendations to promote a parallel planning process along the Pacific coast of North America.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".