Westward Expansion: While the Trains Kept Moving, CPR Built New Capacity in Western Canada To Handle Surging Traffic
Bibliographic record
Abstract
Canadian Pacific is spending $160 million to expand capacity in its western region on tracks and routes crossing the Continental Divide. The last major upgrade happened in the mid-1980s, when the Mount Macdonald Tunnel and the Fox Tunnel were blasted through the Selkirk Mountains in British Columbia. This newest project, called Western Capacity Expansion Project (Westcap) was the beginning of what could be a $500 million investment over the next five to 10 years. It was completed in October 2005, and it serves the rising number of exports from Canada through Vancouver, as well as imported containerized cargo from the Pacific Rim. Capacity is now up to 38 trains a day across the Rocky Mountains, an increase of more than 400 freight cars a day. It was done in the busiest corridor, and it consisted of almost all new construction. The article describes the amount and type of materials used and the scheduling methods to complete work in the short May-October season. Concrete tie laying, for example, had to be done in a way that did not foul adjacent tracks. Photographs depict some of the various installation methods that were used.
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 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.004 |
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".