Integrating Frequent Transit Service and Corridor-Based Transit Supportive Environments inteh Metro Vancouver Region
Bibliographic record
Abstract
Frequent transit networks have been developed in a number of metropolitan areas in North America, Australia, and Europe. TransLink has recently introduced a Frequent Transit Network (FTN) in the Metro Vancouver area. TransLink's FTN is an interconnected network of corridors with transit services operating every 15 minutes or more frequently throughout the day and into the evening every day of the week. As part of its Regional Growth Strategy review process, Metro Vancouver is introducing a concept called Frequent Transit Development Corridors to shape land use in support of provision of frequent transit. TransLink and Metro Vancouver are working together to identify factors and develop policies that will help create a transit-oriented region focused around urban centres and the FTN. Another key tool to support the FTN network is the establishment of transit priority measures on roads to improve service reliability and transit travel time. When all these factors and others are implemented in a coordinated manner, a magnification of transit demand and level of service is possible within the region. The Frequent Transit Network and Metro Vancouver's proposed Frequent Transit Development Corridor concept hold the promise of a bold vision for how to integrate land use, transit supportive infrastructure and frequent transit service. For the region to realize this vision, it will require collaboration and coordinated actions amongst all the key players in the region.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".