Squaring the circle: The BHLS concept
Bibliographic record
Abstract
The transport systems known as Bus Rapid Transit (BRT) was launched in Curitiba, Brazil, in 1974 as a means of offering efficient and effective bus travel within the fast expanding city. This experience, together with other big examples like in Ottawa (since 1983) or in Quito (since 1994), have proven to be an efficient and effective solution to mass transport. Throughout Europe similar experiences have started to be developed, but responding to a different concept of quality of service. Bus systems such as the “trunk network”, in Sweden, the Metrobus, in Germany, or the BHNS (Bus à Haut Niveau de Service), broach the quality of service from a wider perspective than the BRT, as it considers aspects such as image, confort...,apart from speed, frequency or reliability. These new systems - BHLS (Buses with a High Quality of Service) - allow to combine quality of service of tramways with the lower costs and higher flexibility of bus systems, and offers very interesting solutions in terms of accessibility, a wide range of service levels, that allows the system to be adapted to the different urban contexts (size, population, density…) In the economic situation we are now living, the lack of funds provides BHLS an important role in public transport. Less costs with the same quality of service seems to be a very attractive option. The aim of this article is to compare the different European experiences of tramways and BHLS, specially from the economic point of view, considering the costs, benefits and advantages of each of them.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.013 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.034 | 0.011 |
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".