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Record W1993898662 · doi:10.1061/9780784413210.016

Opportunities and Operational Difficulties of Introducing Bus Rapid Transit (BRT) in Dhaka

2013· article· en· W1993898662 on OpenAlexaff
Sudip Barua, Mudasser Seraj, Dhrubo Alam

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsHeadwayBus rapid transitPublic transportOccupancyTransport engineeringTransit (satellite)Service (business)PopulationIntersection (aeronautics)BusinessComputer scienceEngineeringCivil engineering

Abstract

fetched live from OpenAlex

Dhaka is one of the most densely populated cities in the world. The abrupt increase in population along with diverse urban land use patterns has engendered an ample travel demand. In addition, gradual deterioration of level of service of public transport system and increasing private car ownership create acute intolerable congestion. In these circumstances, Bus Rapid Transit (BRT) is one of the most effective short-term solutions because of its high capacity as well as relatively low construction and operating cost. Despite the high opportunities of introducing BRT in Dhaka, it will face some operational difficulties such as high occupancy, high operational fleet size, small headway, priority in intersection and signal control, etc. Results show that to satisfy the projected high passenger demand, the headway will be 16 seconds and operational fleet size; occupancy will be very high in many locations, which will make the BRT operation difficult and ineffective.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.030
GPT teacher head0.253
Teacher spread0.223 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2013
Admission routes1
Has abstractyes

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