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Record W2969753381 · doi:10.1155/2019/4183065

Dynamic Changes in Maritime Research Capability in Chinese Universities

2019· article· en· W2969753381 on OpenAlexvenueno aff
Young-Tae Chang, Ah-Hyun Jo, Kyoung-Suk Choi

Bibliographic record

VenueJournal of Advanced Transportation · 2019
Typearticle
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsnot available
Fundersnot available
KeywordsChinaMainland ChinaRanking (information retrieval)Government (linguistics)Regional scienceGeographyPolitical scienceEconomyBusinessEconomicsComputer scienceArchaeology

Abstract

fetched live from OpenAlex

This study determines the top fifty authors in China and their university affiliations in the maritime transportation field, compared to their world ranking. We refer to China in the broad sense of the Chinese economies, including not only mainland China and Hong Kong, but also Chinese Taipei (Taiwan) and Singapore. This study analyzes sixty-five SSCI and SCI journals in the field of maritime and transportation between the years 2000 and 2015. In terms of ranking, three indicators are employed: total number of articles, weighted score (indication of author contribution), and the impact score. With the exception of Shanghai Jiao Tong University, no other universities selected in the first phase of Project 985, which received billions of dollars in government support/aid, were listed in the world ranking. Star authors are deemed to have contributed greatly to the rankings of their affiliated universities. The future of China’s rankings is bright in view of the increasing number of papers being published by Chinese authors and universities and their strong grounding in quantitative methodologies.

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 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 score0.802
Threshold uncertainty score0.406

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 head0.009
GPT teacher head0.268
Teacher spread0.260 · 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 teacher head, 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

Citations3
Published2019
Admission routes1
Has abstractyes

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