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Record W2014193427 · doi:10.1061/41039(345)458

System Analysis of Air-Rail Inter-Modality Service in Yangtze Delta Area

2009· article· en· W2014193427 on OpenAlexaff
Zhao Yali, Cancan Qin, Ying Hui

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsMinistry of Education and Child Care
Fundersnot available
KeywordsChinaTransport engineeringService (business)AviationDeltaYangtze riverKey (lock)BusinessComputer scienceEngineeringGeography

Abstract

fetched live from OpenAlex

Intercity railway and high-speed railway have been developed in China for a lot of years. The operation speed and level of service have been significantly improved from common railways. Simultaneously, aviation industry is growing up rapidly. Key airports such as Shanghai Pudong International Airport and Hongqiao Airport have amazing growth of patronage and cargo and parcel. In developed areas such as Yangtze Delta Area and Pearl River Area, economic vigor and regional communications lead to a typical trip-chain pattern which is aviation and railway. This paper analyzes traveler's characteristics of this pattern. And some key problems such as demand and service pattern are discussed. Air-rail inter-modality has been developed in Europe for many years. In china, with different mechanism and infrastructure conditions, exploration of its implementation feasibility is also the research purpose of this paper.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.181

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.292
Teacher spread0.270 · 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 designSimulation or modeling
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
Published2009
Admission routes1
Has abstractyes

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