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Transit Smart Solution for Bratislava – Example of Tramway Network Development

2022· article· en· W4307465124 on OpenAlexaff
Tibor Schlosser, Peter Schlösser, M Korfant, Gabriel Bálint, Jakub Takács

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2022
Typearticle
Languageen
FieldEngineering
TopicTransport and Logistics Innovations
Canadian institutionsTransport Canada
Fundersnot available
KeywordsTransport engineeringTask (project management)Public transportCover (algebra)Urban agglomerationWork (physics)Capital cityCapital (architecture)TelecommunicationsComputer scienceArchitectural engineeringBusinessEngineeringGeography

Abstract

fetched live from OpenAlex

Abstract The research presented was on the table more years and covers the cooperation of the University staff with City of Bratislava binding with the activity of private company. The base task was how to change the tremendous destruction of modal split in Bratislava, which growing on the side of private car usage. Results of couple of traffic studies show, that how could be this change re-define the current traffic behaviour and create for the new area new functional interest and certainly the new quality of relationships of land use. The system solution is in the amplification by a capacitive new tramway network. In the conditions of Bratislava, we need to change the behaviour of the people in the mobility over the area of the Capital city of Slovakia. The task was to solve the problem in Bratislava agglomeration as well. The solution is shown as a part of the integrated public transport services possibility to operate regular all days’ mobility problems in the city and not only to cover the rush hours. This article is an overview of 5 years work of traffic engineers and planners to keep clear systematic approach and solutions with developers and municipality administration.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.512

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.031
GPT teacher head0.205
Teacher spread0.174 · 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 designBench or experimental
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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