Ocean Shipping Container Availability Report. October 1, 2014
Bibliographic record
Abstract
The Port of Seattle, WA, ranks 6th in the nation for containerized waterborne agricultural exports; it moved more than 602,000 metric tons of containerized agricultural products from July to September, 2013. Grains, including animal feed and soybeans, accounted for 50 percent, vegetables for 19 percent, and frozen fish accounted for 6 percent of the volume. During this period, more than 53 percent of these agricultural exports were moved in 40ft containers. Agricultural exporters used the ocean carrier Maersk to move 21 percent of these products, followed by Hanjin Shipping at 16 percent, China Shipping at 11 percent, and MOL at 10 percent. 1 Container availability estimates at the Port of Seattle have been quite volatile this summer (see graphic below). Seattle has experienced increased demand from diverted cargo from Los Angeles and Long Beach due to the ongoing labor contract negotiations as well as diverted cargo from Vancouver, BC, due to congestion across the border. Carriers have struggled to balance availability in Seattle, which causes strong weekly fluctuations to container availability estimates. Additionally, for the past 2 weeks (week 39 and 40) one participating carrier switched service from Seattle to Tacoma due to congestion at the port and to provide a more efficient service schedule. The availability of 40ft refrigerated containers has been particularly strong the past few weeks, probably filling demand for increased fruit and vegetable exports from Washington at this time of year. Carriers anticipate estimates will decrease the next 2 weeks for 40ft standard, high-cube, and refrigerated containers but increase for 20ft standard containers. Weekly Container Availability Estimates in Seattle, 2nd week of July (Wk 28) through 1st week of October (Wk 40), with Projections Location Specific
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".