Scenario Analysis of Containerized Freight Distribution into the Midwest Region in Response to Capacity Expansions
Bibliographic record
Abstract
The U.S. major ports receive more than 50% of total container freight from seven Asian trading partner countries and redistribute to the states. The Panama Canal and the port of Prince Rupert in Canada will double their capacity from 2015 and 2020 and assuming to change receiving calls at ports from current status. Based on the current container freight flow between the Asian countries and the U.S. states, two capacity expansion scenarios are additionally considered for optimal distribution of containerized cargo into the U.S. With a non-linear optimization process, import container cargo distributions into the Midwest Regions are estimated under current capacity and increased capacity for both the Panama Canal and Prince Rupert expansions. Scenario comparison resulted that the Panama Canal expansion changed flow into the Midwest Regions from the West and Gulf Coast ports, but Prince Rupert capacity increase affected little flow changes.
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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 | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".