Off-Dock Storage of Empty Containers in the Lower Mainland of British Columbia
Bibliographic record
Abstract
BC’s Lower Mainland is Canada’s largest gateway for international container traffic. There are four deepsea container terminals. The terminals are geographically dispersed, with two in the Port of Vancouver’s Inner Harbour, one on Roberts Bank, and one located on the Fraser River under the jurisdiction of the Fraser River Port Authority. In December 2003 the Vancouver Port Authority announced a target of moving 50 % of empty containers to off-dock storage. A draft protocol for achieving this target was developed, but following consultations formal implementation was deferred due to concerns expressed by port stakeholders. However, whether through the Vancouver Port Authority initiative or as a response to short term congestion problems at the terminals, the use of off-dock facilities for storage of empty containers in the Lower Mainland has increased. This has imposed additional costs on shipping lines, trucking companies and drivers. Trip patterns and compensation have traditionally been based on round trips to and from the deepsea container terminals. The introduction of off-dock storage introduced a non-revenue “third leg ” to truck trip patterns. Due to the geographical dispersion of the deepsea and off-dock container yards, and to contractual arrangements
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".