Bibliographic record
Abstract
This article describes how Canadian Pacific (CP) is riding the wave of North American oil producers' because these producers are increasingly relying on rail to transport their crude oil to the U.S. Gulf Coast and Northeast refineries. In order to get a sense of how quickly the crude-by-rail business has grown for the Class I, consider this: CP moved 500 carloads of crude oil in 2009, 13,000 in 2011 and more than 53,000 in 2012. In January, the railroad reached a 70,000 annual carload run rate for crude oil, a rate met much earlier than expected. With each car holding about 650 barrels, that's a lot of crude. The Class I is expecting the growth to continue throughout this year. Beyond 2013, the railway has a line of sight that is two to three times the present volume going forward. This is a very positive story for the company. CP executives reported during the Class I's fourth-quarter 2012 earnings teleconference that crude by rail represents the Class I's strongest opportunity for traffic and revenue growth.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.029 | 0.005 |
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".