A Systems Approach for the Evaluation and Rebuilding of the Rogers Pass Systems on Canadian Pacific
Bibliographic record
Abstract
Abstract In the 1980’s, Canadian Pacific (CP) constructed one of the most ambitious projects since the original completion of the railway in 1885. The Rogers Pass project was initiated at CP in the early 1980’s to allow for increased capacity and efficiency by installing a second main track within the Rogers Pass area. Completed in 1988, the Rogers Pass Project included the construction of a new line with significantly lower westbound grades and two tunnels with a combined length of over ten miles. Several other systems were required to complete the project that will be discussed I this paper. Recently, CP has started a new Multi-Year Plan to rebuild virtually all of the tunnel systems infrastructure that will not only prolong the life of these systems, but will introduce technology not known at the time of construction. These new systems will enable CP to greatly reduce maintenance cost while improving reliability. These systems include a high voltage transmission line that feed the ventilation house, a sophisticated ventilation system that allows fresh combustion air to reach the locomotives working the uphill grades, as well as process controllers that automate all of these systems. As all of the systems are reaching the end of their useful life, CP’s rebuilding will also increase overall system capacity.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".