Pedestrian Route Choice of Vertical Facilities in Subway Stations
Bibliographic record
Abstract
Transit infrastructure is under pressure. As the trends toward greater urbanization and more sustainable mobility continue, that pressure is likely to increase. Finding ways to accommodate passengers more effi-ciently in existing transit facilities will become of ever greater importance, as will the tools and techniques to assess pedestrian movement. The suite of pedestrian analysis tools is reliant on first principles knowledge and research, where gaps exist. This paper describes research that has been completed to fill one such gap, namely rider choice at vertical circulation. First, field research was conducted on the Toronto Transit Commission subway system in Canada. Key explanatory variables were then tested for significance, including total height, density of flow, rate of opposing flow, and mobility of the individuals. On the basis of this analysis, a series of aggregate logistic regression models is proposed to explain pedestrian choice at colocated elements of vertical transport, specifically, stair-versus-escalator choice. Validation data indicate that the model generates values that provide a good fit with observed data.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".