Operational Development of Marine Highways to Serve the U.S. Pacific Coast
Bibliographic record
Abstract
This paper examines the market volumes, service times, vessel characteristics, and economics for marine highways that would serve the U.S. Pacific Coast. This work was performed under contract to the Center for Commercial Deployment of Transportation Technologies. Market volumes were assessed by routes of interest and by filtering for cargo that would be eligible for marine highway service on the basis of the drayage distance and other factors. Sufficient daily truckload volumes exist in the Northern California to Southern California route to justify marine highways with multiple daily sailings of vessels with capacities of 450 to 700 trailers, should service times and economics prove to be competitive enough to divert cargo. Market volumes in the California to Pacific Northwest route are sufficient for daily sailings of smaller vessels with capacities of approximately 150 to 200 trailers. A door-to-door supply chain perspective was maintained, and discrete-event simulation was used to assess the service times and the vessel speeds required. The resulting voyage analysis served as input to both a parametric analysis of vessel characteristics and an economic analysis of marine highways by considering all maritime and land-side cost elements associated with the door-to-door movement of trailers. It was concluded that current truck rates are not high enough for marine highways to compete on the basis of cost in short next-day-turnaround markets, such as Northern California to Southern California. Marine highways are viable for longer routes such as those from California to the Pacific Northwest, where truck rates are higher and both distance and trucking hours-of-service regulations permit vessels to be time competitive at lower speeds.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".