Bibliographic record
Abstract
ABSTRACT An issue of increasing concern worldwide is that of oil spills from nontank vessels that carry large quantities of petroleum product as fuel or lubricants. The New Carissa incident in Oregon in 1999 is only one of several that have impacted the U.S. West Coast in the last few years. Others include the M/V Kuroshima, which grounded in Dutch Harbor, Alaska in 1997, and the M/V Kure, which spilled oil in Humbolt Bay also in 1997. The Tenyo Maru was cut in half in a collision and sank with the loss of one life and a spill of at least 100,000 gallons of heavy fuel oil and diesel in Washington State in 1991. Additional examples of both spills and threats of spills are sited, both in the United States and worldwide. This paper examines a number of actions that have been taken in response to this threat. One such model is the Canadian requirement that vessel owner/operators demonstrate a formal agreement with an approved response contractor, and list that contractor in their Shipboard Oil Pollution Emergency Plan (SOPEP). A more comprehensive approach would be to establish approved “umbrella” contingency plans for major port areas, supported by contracts with oil spill removal organizations (OSROs). This preferred model has been adopted by the U.S. West Coast states, and affords the opportunity for the contracted responders to drill with emergency response officials, thus improving the likelihood of an efficient, coordinated spill response. This paper also proposes spill prevention design elements for nontank vessels.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".