Impacts of Panama Canal Expansion on U.S. Greenhouse Gas Emissions
Bibliographic record
Abstract
International shipping is a significant contributor to global climate change, accounting for approximately 3.3% of global carbon dioxide (CO 2 ) emissions across all sectors. The expansion of the Panama Canal, scheduled to open in 2014, will improve available all-water routes for trade between the eastern United States and Asia, creating opportunities for both lower emissions and lower costs. The authors used data from the import and export projections of the FHWA Freight Analysis Framework 3 database to estimate the canal's impact on shipping emissions with and without the expansion project. The expansion is expected to reduce annual CO 2 emissions of U.S. East Coast–Asia trade by 1.4 billion kg in 2025, a per ton reduction of 2.69%. Along with design and operational improvements, the efficiencies created by increased opportunities for use of all-water routes and large vessels are expected to have a small but beneficial impact on greenhouse gas reduction efforts in international shipping.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".