Urban development with financially sustainable rail service
Bibliographic record
Abstract
Summary The positive correlation between urban population density and transit service patronage is well recognized, as was ascertained via statistical approaches in previous studies. In this study, we seek to derive some prescriptive results of the relationship between urban population density and the financial sustainability of rail transit service via analytical approaches. We consider an idealized metropolitan region with a central business district at its center, whose population is distributed according to a certain density saturation gradient pattern. Trips generated from the region to the central business district are served either by the rail service supplemented with feeder buses or by autos. Travelers choose one of the two modes to minimize the travel cost. The traffic congestion effects on highway system for auto users will be considered by assuming flow‐dependent travel time delay. The crowding costs of transit services will also be taken into account. The spatial equilibrium travel pattern with modal choices will be modeled by applying a differential equation approach. Then, we study the sensitivity of urban development density on the financial sustainability of the rail service by examining the supply and demand patterns. Through the analysis, the result sheds light on the threshold urban density required, below which the service cannot be sustained financially. The results also provide guidelines for planning urban development with financially sustainable rail services. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".