Bus and Rail Transit Preferential Treatments in Mixed Traffic
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.
Bibliographic record
Abstract
This synthesis provides a review of the application of a number of different transit preferential treatments in mixed traffic and offers insights into the decision-making process that can be applied in deciding which preferential treatment might be the most applicable in a particular location. The types of preferential treatments covered include median transitways, exclusive transit lanes, stop modifications, transit signal priority, special signal phasing, queue jump lanes, and curb extensions. The synthesis is offered as a primer on the topic area for use by transit agencies, as well as state, local, and metropolitan transportation, traffic, and planning agency staffs. This synthesis is based on the results from a survey of transit and traffic agencies related to transit preferential treatments on urban streets. Survey results were supplemented by a literature review of 23 documents and in-depth case studies of preferential treatments in four cities -- San Francisco, Seattle, Portland (Oregon), and Denver. Eighty urban area transit agencies and traffic engineering jurisdictions in the United States and Canada were contacted for survey information and 64 (80%) responded. One hundred and ninety-seven individual preferential treatments were reported on survey forms. In addition, San Francisco Muni identified 400 treatments just in its jurisdiction.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it