FREIGHT MOVEMENT LOGISTICS AND THE RESPONSE OF BUSINESSES TO HIGHWAY CONGESTION
Bibliographic record
Abstract
During the month of June 1999, in-depth interviews were conducted with representatives of sixty-one businesses in the metropolitan area that includes Portland, Oregon and Vancouver, Washington. This paper summarizes the lessons learned about the logistical decision making from those interviews. The purpose of the interviews was to gain information about freight and goods movement in the Portland area that would help the region's transportation agencies identify freight related needs in the I-5 Corridor and other parts of the region's transportation system. The interviews were designed to gain a better understanding of how level of service on the area highways affects the logistical decisions and costs of the area's shippers and carriers. The interviews will also be used to confirm and calibrate the region's commodity flow and freight movement forecasting model. The interviews were also designed to help identify where roadway congestion is seriously affecting area businesses and improvements the business community would most like to see funded.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".