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Record W632424434

TERMINAL CAPACITY : NORTH AMERICAN RAILROADS WILL NEED MORE OF IT TO HANDLE TODAY'S - AND TOMORROW'S - INTERMODAL TRAFFIC

2005· article· en· W632424434 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProgressive railroading · 2005
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicTransport and Economic Policies
Canadian institutionsnot available
Fundersnot available
KeywordsBoomTransport engineeringTerminal (telecommunication)TrailerEngineeringContainer (type theory)EconomyBusinessTelecommunications
DOInot available

Abstract

fetched live from OpenAlex

Railroads in North America are experiencing a boom in intermodal traffic, leading industry analysts to forecast a 3.8% increase in 2005 in their trailer and container movements as compared to 2004. One of the primary reasons for this growth in intermodal traffic is the big influx of traffic from Asia. This rise in intermodal shipments, however, is weighing heavily on the terminal capacity of roads, which in turn has prompted the railroads themselves to build their own intermodal facilities, or expand existing ones. This article looks at various railroads and their capacity expansion efforts. Kansas City Southern (KCS), known as the NAFTA Railroad, is focusing on building terminals in the U.S./Mexico border region. Other railroads profiled include Burlington Northern Santa Fe(BNSF), Canadian National Railway (CN), and Florida East Coast Railway (FECR).

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.234
Teacher spread0.219 · 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