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Record W4254189127 · doi:10.32920/ryerson.14644503

BRT omnibus : how bus rapid transit enhances mobility

2021· preprint· en· W4254189127 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicUrban Transport Systems Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBus rapid transitPopularityFlexibility (engineering)Transit (satellite)Mode (computer interface)Transport engineeringComputer sciencePublic transportBusinessEngineeringEconomicsPolitical science

Abstract

fetched live from OpenAlex

<p>Bus Rapid Transit (BRT) has emerged in the 21st century as a leading form of building rapid transit in urban environs due to their ability as a rapidly implementable, relatively low-cost, flexible, and high-quality transit mode. While the popularity of the BRT mode continues to grow worldwide, there remains a degree of uncertainty over what designing for success looks like for BRT systems. This paper sought to determine whether there was a "correct" design approach for BRT implementation through literature review and case study. The case study revealed that despite differences in design and implementation, the cases successfully attained their respective planning and performance objectives. The inherent flexibility of the BRT mode allowed for BRT systems to be scaled to a wide array of operating and ridership contexts, as well as allow for incremental enhancements to the system as the passenger demands, available financing, and political will for upgrades arise. </p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.012
GPT teacher head0.188
Teacher spread0.176 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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