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Record W3215442565

High speed railway and metropolitan integration in Spain: the case of Ciudad Real and Puertollano

2019· article· en· W3215442565 on OpenAlexaboutno aff
José María Ureña

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicAviation Industry Analysis and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsMetropolitan areaGeographyPopulationQuarter (Canadian coin)Service (business)Regional scienceTransport engineeringEconomyDemographySociologyEngineeringArchaeologyEconomics
DOInot available

Abstract

fetched live from OpenAlex

Ciudad Real and Puertollano, two small Spanish cities approximately one hours travelling time from Madrid on the Madrid-Sevilla High Speed Train (HST) line, are of particular interest in the study of the impact of HSTs on such centres of population. Both cities had been separated from the main transportation corridor between Madrid and Andalusia since the end of the 18th Century and, at the end of 1992, the HST line reintegrated them into this corridor. That same year the Autopista de Andalucia (Andalusia Freeway), whose route runs some 50 kilometres to the east of Ciudad Real and Puertollano, entered into service. The current article has three basic objectives. The first one is to determine the most appropriate type of methodology to analyse the effect produced by an HST ten years after its inception. The second is to describe the observed changes in the mobility patterns of the inhabitants of Ciudad Real and Puertollano. The article concentrates on the employment profile and the frequency of use of those who habitually travel on the HST to and from Madrid. Thirdly, the article analyses the role the HST has played firstly in integrating the two cities with each other, and secondly in integrating both with the metropolitan area of Madrid. It then analyses the distinct effects of each of the two transport routes (freeway and HST) on each of the two cities, paying attention to their economic peculiarities (Ciudad Real being a tertiary city and Puertollano being an industrial one).

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 score0.671
Threshold uncertainty score0.997

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)0.0010.000

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 head0.023
GPT teacher head0.230
Teacher spread0.208 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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