Bibliographic record
Abstract
For generations, the transit industry has had to balance the desire for faster boarding with the need to collect fares. On July 1, 2012, the San Francisco Municipal Transportation Agency (SFMTA) in California addressed this challenge by becoming North America's first multimodal transit operator to implement all-door boarding systemwide. Customers with valid fare media may enter through any door of any vehicle at any time. Unlike other transit providers that used proof of payment, SFMTA still allowed customers to pay cash on board vehicles at surface stops, thus avoiding the expenses associated with wayside ticket vending machines. San Francisco's operating environment provided ideal conditions to demonstrate the potential benefits of all-door boarding. Serving the nation's second-densest major city with crowded transit vehicles largely operating in mixed traffic, SFMTA must make efficient use of every minute in revenue service and cannot afford excessive time at stops. Two years after the policy's implementation, a comprehensive and multi-factor analysis revealed incremental improvements in dwell times and fare compliance. Overall bus speeds increased slightly despite ridership growth and a population and employment boom.
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How this classification was reachedexpand
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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".