Urban Public Transport as a Basis for Sustainable Mobility Development in the Transition from Private Vehicles to Urban Public Transport: A Case Study of Elbasan
Bibliographic record
Abstract
This study is aimed at evaluating the functionality of urban transport terminals in Elbasan City, identifying potential shortcomings in their modernization process, and providing actionable recommendations to enhance the quality of urban transit services.The study also investigates the challenges and impacts associated with transitioning from private vehicles to urban public transport systems within the city.Various research methods, including analytical, classification, functional, and statistical approaches, were employed.The research scrutinizes the unique aspects of the city's urban functioning and pinpoints the errors made during terminal modernization, further exploring their underlying causes.It also examined strategies to improve transport mobility.Analyzing the system's operation is crucial to understanding its effectiveness, growth, and the complexities associated with the shift from private cars to urban public transport in Elbasan.This research also evaluates urban transport terminal-related concerns, their importance in the context of urban transport, and their implications.Based on the findings, recommendations were proposed to address these concerns.The study's findings underscore the importance of enhancing urban public transport.It highlights that boosting the transportation potential is not only crucial for meeting the community's transportation needs but also plays a pivotal role in advancing logistics.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".