LRT passengers’ responses to advanced passenger information system (APIS) in case of information inconsistency and train crowding
Bibliographic record
Abstract
This research explores and attempts to understand transit riders’ behavioural responses towards real-time transit information for two specific situations: the presence of inconsistent information on transit service recovery and the effects of crowded trains during rush hours. A survey was designed and conducted to collect light rail transit (LRT) riders’ behavioural responses in Calgary, Alberta. Multinomial logit models were developed and calibrated to explore the effects of the described scenarios on riders’ responses. The results led to the conclusion that socioeconomic attributes, experience with advanced passenger information system (APIS) system, familiarity with public transit in general and Calgary’s LRT system in particular, and the characteristics of origin LRT stations had strong influences on travellers’ behavioural responses. It was also determined that travellers’ actions vary significantly depending on the purpose of the trip, time of the trip, and weather conditions.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".