An Examination of the Public Transport Information Requirements of Users
Bibliographic record
Abstract
This paper focuses on the provision of public transport information in Dublin, Ireland. It examines both existing and potential methods of accessing information, with particular focus on the implementation of various intelligent transport systems applications. One of the main objectives of this paper is examining the stages a passenger goes through when deciding to undertake a public transport trip and in what form they require information at each stage. This paper defines these stages as "pre-trip to destination," "at-stop," "onboard," and "pre-trip to origin" (this is the return journey). Each of these four stages is examined in this paper. A web-based survey was used to collect data on passenger preferences and describes the methods of information delivery each passenger requires at each stage. This paper primarily deals with the respondents' stated preference for public transport information and does not examine revealed preferences. The survey also details results of passengers' opinions of the different information provision formats such as call centers, mobile phones, the Internet, and paper-based methods. This paper concludes with the results of this exploratory research
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".