The analysis of disused railway lines as complex systems: GIS-based inventory and comprehensive analysis method
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".