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Record W2790270891 · doi:10.3917/pe.181.0119

Nouvelles liaisons ferroviaires chinoises : une entreprise stratégique

2018· article· fr· W2790270891 on OpenAlexaff
Linyan Huang, Frédèric Lasserre, Éric Mottet

Bibliographic record

VenuePolitique étrangère · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicChina's Global Influence and Migration
Canadian institutionsUniversité du Québec à MontréalUniversité LavalFrancophone University Association
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Depuis 2011, le fret ferroviaire entre la Chine et l’Europe s’est rapidement développé, et a connu une relance spectaculaire avec le projet Belt and Road Initiative. On assiste aujourd’hui à une rapide expansion des volumes, des services proposés, le tout accompagné par la définition et la mise en œuvre de nouvelles infrastructures ferroviaires, en Russie, en Chine, vers l’Asie du Sud-Est, l’Iran ou le Pakistan. Ce développement, qui doit être nuancé, constitue-t-il un outil stratégique pour la Chine ?

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)0.002
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.123
Threshold uncertainty score0.244

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0100.004
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.020
GPT teacher head0.324
Teacher spread0.303 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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