Development of the Adoption of Liquefied Natural Gas as a Fuel for Shipping on the Great Lakes
Bibliographic record
Abstract
The adoption of the International Maritime Organization's emission control areas by the United States and Canada compelled operators of short sea vessels on the Great Lakes to seek alternatives to current fuel usage. Because of the concurrent discovery and extraction of large quantities of natural gas in the United States and Canada, ship owners have the opportunity to switch to natural gas. Converting to a new fuel is a complex process involving research and changes in operations, engineering, supply chains, and training. The Great Lakes Maritime Research Institute has been involved in a multiyear study supported by government agencies and industry to prepare for the adoption of natural gas as a primary fuel for U.S. vessels on the Great Lakes. This paper discusses the research process, including marine engineering studies, vessel operational issues, investigating regulatory issues, the development of supply chains, public outreach, and the analysis of fuel alternatives for vessels. The environmental benefits that accrue from conversion, as well as the potential operational costs, are compared. Steps in the conversion process, including siting of natural gas liquefaction plants and fuel taxation, are proposed.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".