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Record W281793536

North American transportation corridor network

2007· article· en· W281793536 on OpenAlexaboutno aff
Juan Carlos Villa, Christopher W Rothe

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Relations in Latin America
Canadian institutionsnot available
Fundersnot available
KeywordsPort (circuit theory)Government (linguistics)Transportation planningFlow networkTransport networkGeographyTransportation infrastructureTransport engineeringState (computer science)Plan (archaeology)Regional scienceBusinessEngineeringComputer scienceArchaeology
DOInot available

Abstract

fetched live from OpenAlex

Trade flows across the three North American countries have increased substantially since the implementation of the North American Free Trade Agreement (NAFTA), but there is no movement toward developing a true North American Transportation Corridor Network. This report examines two types of North American transportation corridor networks. The first is a transportation infrastructure network that spans across the three North American countries, including highways, railroads, and port of entries which are all part of a large multimodal transportation network. The second type of network analyzed, is a research network that is a collection and collaboration of organizations, individuals, and research that have the goal of improving transportation in North America. Through this research project, a group of transportation experts from the United States, Mexico and Canada was assembled through a webinar to discuss issues related to a North American transportation corridor plan. The formation of a North American transportation center is recommended to research and educate government officials on the current and projected state of transportation in North America.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.885
Threshold uncertainty score0.392

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.008
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.1170.022

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 head0.011
GPT teacher head0.327
Teacher spread0.315 · 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 designObservational
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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Same topicInternational Relations in Latin AmericaFrench-language works237,207