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The Emergence of Trans-Asian Rail Freight Traffic as Part of the Belt and Road Initiative: Development and Limits

2020· article· en· W3036846848 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChina Perspectives · 2020
Typearticle
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsUniversité du Québec à MontréalUniversité LavalNatural Sciences and Engineering Research Council of Canada
Fundersnot available
KeywordsChinaTrainRail freight transportFreight trainsPoliticsBusinessTransport engineeringTraffic volumeRail networkEconomyRegional sciencePolitical scienceEngineeringEconomicsGeography

Abstract

fetched live from OpenAlex

Since 2011, freight transport rail links between China and Europe have been rapidly multiplying. Against all expectations, this commercial initiative, under the aegis of the Deutsche Bahn, has expanded significantly. The number of origin-destination pairs has increased, the number of trains has risen sharply, and both Chinese and European partners have far-reaching ambitions. The railways’ market share of trans-Asian freight is still low. However, rail link development projects have received a spectacular boost from the Belt and Road Initiative (BRI), resulting in the rapid expansion of volume, services offered, and the emergence of new rail infrastructure. Does this development, which needs to be examined more closely, represent a political tool for China? To what extent does the development of these rail links rely on a buoyant market? This article studies the development of rail services and infrastructure by means of a cross-analysis of a body of technical reports and publications by the transport sector’s professional press.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.887
Threshold uncertainty score0.247

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 communication0.0000.000
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 head0.019
GPT teacher head0.213
Teacher spread0.194 · 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