The West Coast Offshore Vessel Traffic Risk Management Project
Bibliographic record
Abstract
ABSTRACT The West Coast Offshore Vessel Traffic Risk Management Project resulted from a unique collaboration between the US Coast Guard Pacific Area, the Canadian Coast Guard, and the environmental agencies representing the Province of British Columbia and the States of Alaska, Washington, Oregon, and California. In addition to these organizations, the Project Workgroup included federal military and environmental agencies from both the US and Canada, industry from all the affected regions, as well as public interest organizations. The primary focus of the project is prevention of drift groundings - and subsequent oil spills - by disabled vessels traveling coastwise off the West Coast of the US and Canada anywhere between Cook Inlet and San Diego. Working together over a three-year period, the Project Workgroup collected information on West Coast traffic patterns, traffic volume, existing management measures, ship drift rates, historical casualty data, weather data, assist vessel availability, and economic and environmental sensitivity of the coastlines. Vessel types of concern included laden tank vessels and barges, plus cargo, passenger, and fishing vessels over 300 gross tons. Two risk assessment tools were developed that incorporated this information and delineated average and higher risk areas of operation on the West Coast. Based upon these outcomes, the Workgroup has developed findings and recommendations focused on reducing risk associated with the distance offshore, collision hazard, tug availability, and historic casualty factors. In addition to the collaborative partnerships involved in this project, the risk assessment techniques and the regional applications are unique and provide a model which could be applied to offshore regions worldwide.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".