Bus Rapid Transit Applications Phase 2
Bibliographic record
Abstract
In February 2010, the Florida Department of Transportation (FDOT) District 4 Office tasked Kittelson and Associates with preparing the Bus Rapid Transit (BRT) Applications Phase I report. That report discussed in general terms the characteristics, system costs, and funding opportunities for BRT. It also described the running way types used by several BRT systems in the U.S. and Canada. Finally, it summarized six previous BRT related studies for South Florida. The District 4 Office has now asked the National Bus Rapid Transit Institute at the University of South Florida and Parsons Brinckerhoff to prepare the BRT Applications Phase II report. This effort is intended to provide a detailed summary of various U.S. BRT systems and to support development of BRT in correlation with the Broward Metropolitan Planning Organization (MPO) 2035 Long Range Transportation Plan (LRTP). There are eight BRT systems included in this report. They include the Cleveland HealthLine, the Eugene EmX, the Kansas City MAX, the Los Angeles Metro Rapid system and Orange Line, the San Pablo Rapid, the Boston Silver Line, and the Las Vegas MAX. The summary for each system has six parts: project background, costs, before and after performance, system characteristics, lessons learned, and future plans. Under system characteristics, information is provided on the running way, stations, vehicles, method of fare collection, Intelligent Transportation System (ITS) technologies, service and operations, and branding.
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 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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.126 | 0.078 |
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".