Semi‐dynamic traffic assignment model with mode and route choices under stochastic travel times
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Bibliographic record
Abstract
SUMMARY Transportation network conditions vary significantly during the course of a day. In many urban areas, public transit and (private) automobiles constitute the actual forms of transportation that use such networks. Public transportation by rail is more reliable than by automobiles or buses; therefore, ordinary static and deterministic traffic assignment models with combined mode and route choices may not be suitable to assess a transportation network that includes public railways. Moreover, within‐day dynamics and reliability need to be incorporated in such a model. In this paper, we use a semi‐dynamic traffic assignment model that considers within‐day dynamics by improving the static traffic assignment model. In addition, stochastic travel times are incorporated into the model. Thus, we propose a semi‐dynamic traffic assignment model with mode choice between public transit and automobiles, route choice with stochastic travel times, and an accompanying computing algorithm. This model enables us to assess within‐day dynamics of transportation networks and travel time reliability of public railways. Copyright © 2012 John Wiley & Sons, Ltd.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it