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Record W596013841

Canadian International: The Making of One Transportation Company's Global Strategy

2007· article· en· W596013841 on OpenAlexaboutno aff
Pat Foran

Bibliographic record

VenueProgressive railroading · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsnot available
Fundersnot available
KeywordsTrainPort (circuit theory)Service (business)Investment (military)BusinessLogistics centerChinaExcellenceTelecommunicationsTransport engineeringEconomyFinanceEngineeringMarketingEconomicsGeographyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Canadian National Railway Co. is expanding its rail network and also adding new services such as freight forwarding and logistics to its business offerings. With its purchase in 1998 of Illinois Central Corp., it became the only rail network in North America to connect three coasts: the Pacific, Atlantic and Gulf of Mexico. Since then, it has expanded and improved its intermodal service with its Intermodal Excellence (IMX) program, which uses precision railroading, regularly scheduled trains that leave at predetermined times, to draw new customers. The ports of Vancouver, Halifax and Montreal and their connections to the U.S. Midwest are core territories for IMX. Now Canadian National has created CN Worldwide, which links the rail network to European and, more recently, Asian markets. CN now has offices in major Chinese port cities, with some 100 employees around the world in its supply chain/integrated transportation services company. It has also stepped up its investment in warehousing and transloading facilities with a new center at the new Port of Prince Rupert in Prince George, B.C.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.079
Threshold uncertainty score0.574

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0120.003
Scholarly communication0.0160.005
Open science0.0020.004
Research integrity0.0070.005
Insufficient payload (model declined to judge)0.0360.009

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.

Opus teacher head0.027
GPT teacher head0.267
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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