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Record W2893573364 · doi:10.1155/2018/2051606

Study on the Equilibrium Discriminant Model of Urban Agglomeration Transport Supply and Demand Structure

2018· article· en· W2893573364 on OpenAlexvenueno aff
Zhenyu Liu, C. B. Li, Meiying Jian

Bibliographic record

VenueJournal of Advanced Transportation · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsEconomies of agglomerationUrban agglomerationEntropy (arrow of time)Supply and demandUrban structureEconomicsGeneral equilibrium theoryMicroeconomicsEconomic geographyEngineeringUrban planningCivil engineeringThermodynamicsPhysics

Abstract

fetched live from OpenAlex

In order to study the adaptability of urban agglomeration transport supply and demand structure, and to provide the basis for decision-makers when optimizing the structure of transport supply and demand in urban agglomeration, this paper proposed and verified a structure equilibrium theory on the basis of entropy theory. Firstly, based on the analysis of the influencing factors, an urban agglomeration transport demand structure model was established using entropy theory. Secondly, according to the actual passenger and freight turnover of urban agglomeration, a transport supply structure model was proposed with entropy theory. Then, by comparing the two entropy models, the equilibrium state of an urban agglomeration transport structure was analyzed. Finally, HuBaoOr urban agglomeration was taken as an example to verify the science and effectiveness of this discriminant model. The research in this paper lays a theoretical foundation for the achievement of urban agglomeration transport equilibrium structure and for realizing the best economic benefits and social benefits.

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 score0.796
Threshold uncertainty score0.319

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 communication0.0000.001
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 head0.020
GPT teacher head0.290
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 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

Citations4
Published2018
Admission routes1
Has abstractyes

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