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Record W4307811460 · doi:10.1155/2022/3785474

Impact of Change of the Interlocking on the Acceleration of Railway Transport: A Case Study from the Podbrezová Railway Station

2022· article· en· W4307811460 on OpenAlexvenueno aff
Adrián Šperka, Michal Valla, Eva Nedeliaková, Juraj Čamaj

Bibliographic record

VenueJournal of Advanced Transportation · 2022
Typearticle
Languageen
FieldEngineering
TopicTransport and Logistics Innovations
Canadian institutionsnot available
FundersEuropean Regional Development Fund
KeywordsInterlockingTrack (disk drive)Transport engineeringAccelerationInterval (graph theory)EngineeringLine (geometry)Transport systemPoint (geometry)Automotive engineeringComputer scienceMechanical engineering

Abstract

fetched live from OpenAlex

Accelerating rail transport is a key factor in improving the quality of passenger and freight transport. The main research question of the article asks whether it is possible to increase the speed due to the change in the interlocking. The main research tool is a comparison of the interval of crossing before and after the reconstruction of the interlocking. As the entire research is carried out on a single-track line at the Podbrezová station, the interval of crossing is the most relevant indicator. An associated goal of the entire research is to point out a possible increase in the carrying out of station tracks and an overall improvement in the working conditions of operational staff (station inspectors and switchmen).

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 score0.898
Threshold uncertainty score0.341

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.055
GPT teacher head0.291
Teacher spread0.237 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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