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Record W2899248822 · doi:10.1155/2018/3754205

An Evaluation Method of Urban Public Transport Facilities Resource Supply Based on Accessibility

2018· article· en· W2899248822 on OpenAlexvenueno aff
Chao Sun, Michael Zhang, Ze Huang

Bibliographic record

VenueJournal of Advanced Transportation · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsPublic transportTransport engineeringResource (disambiguation)Service (business)Level of serviceBusinessResource allocationEnvironmental economicsComputer scienceEngineeringEconomicsMarketing

Abstract

fetched live from OpenAlex

The two indices of the supply level of urban public transport facilities resource and the public transport-private cars traveling time ratio are used to evaluate the public transport accessibility in urban networks. An evaluation method for urban public transport facilities resource supply is proposed based on accessibility by taking Shenzhen as the research area and by using the London PTAL evaluation system. The method takes into account the walking time outside the public transit station and the spatial layout of public transit stations, reflects regional development opportunity, and can reflect regional differences regarding public transport facilities resources in various spatial scales. This paper evaluates the relative service competiveness of public transports and private cars in the entire travel of individuals based on the public transport-private cars travelling time ratio, which lays a foundation to judge the service level of public transport and to make a purpose-specific transportation policy and public transport development scheme.

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)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score0.714

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.370
Teacher spread0.329 · 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

Citations36
Published2018
Admission routes1
Has abstractyes

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