The Viability and Contribution of High-Speed Rail to the Economic Growth and Social Development
Bibliographic record
Abstract
The United Arab Emirates, located in the southwest of Asia, and Abu Dhabi, is the largest emirate in the United Arab Emirates (UAE). The emirate comprises a total area of 87% of the UAE. In 2009, The Department of Transport (DoT) announced the Surface Master Plan: A vision for connecting Abu Dhabi in 2030. One of the significant economic objectives of the master plan is to boost economic competitiveness through effective freight and passengers transport services. The rapid development and growth in the emirate will result in a considerable increase in freight movement. Thus, investing in high-speed rail (HSR) projects is crucial to achieving the vision objectives. This study seeks to assess the impact of the Etihad High-Speed Rail (ER) project on the economy and sociability in the United Arab Emirates. In addition, the study will review the HSR project’s impact from different studies across the world. The aim will be to synthesize the current knowledge on the subject and draw on the best conditions in which the country can invest in HSR extensions and new projects.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".