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Record W2583208738 · doi:10.2495/sdp-v12-n6-1018-1031

The analysis of disused railway lines as complex systems: GIS-based inventory and comprehensive analysis method

2017· article· en· W2583208738 on OpenAlexvenueno aff
Arritokieta Eizaguirre‐Iribar, Lauren Etxepare Igiñiz, Rufino J. Hernández-Minguillón

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2017
Typearticle
Languageen
FieldEngineering
TopicUrban and Freight Transport Logistics
Canadian institutionsnot available
FundersEusko Jaurlaritza
KeywordsGeographic information systemTransport engineeringComputer scienceInventory analysisCivil engineeringEngineeringConstruction engineeringGeologyRemote sensingProduction (economics)

Abstract

fetched live from OpenAlex

Many kilometres of railway lines are disused in territories where the railways had been dependent on industrial development. The current broad concept of heritage and its territorial character make the proposition of these lines as territorial structuring systems possible. Nevertheless, most of the actions for their protection, restoration or enhancement are fulfiled in some isolated elements, not attempting to understand the line as a territorial system that is formed not only by the nodes but also by the connecting thread. Furthermore, the passage of time and the lack of use have made many heritage elements be in danger of disappearing, if not already disappeared. In this regard, this article emphasizes that the analysis of the disused railway lines should be performed with a comprehensive vision in order to achieve the same results for their protection or for future interventions. This paper aims to create a GIS-based inventory and a comprehensive analysis method for the characterization and classification of disused railway lines of a territory, understanding them as complex systems. The way to address the issue is to avoid the decomposition of the system and favour the maintenance of the structuring nature that the railway lines originally had in each territory, which is one of the most important features for their possible reuse in the new territorial view of the 21st century. In this way, the proposed methodology has been applied on the disused railway lines of the Basque-Navarre territory.

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 score0.280
Threshold uncertainty score0.366

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.046
GPT teacher head0.296
Teacher spread0.249 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

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