Responses to Centre Street Bridge Closure: Where the “Disappearing” Travelers Went
Bibliographic record
Abstract
An ongoing topic of interest in urban transportation engineering is the impact of changes in road network capacity on the amount of vehicle travel in an urban area. In many cases, the debate focuses on potential increases in vehicle travel that occur with increases in road capacity—the phenomenon of “induced demand.” Some studies have also looked at the effects of reductions in roadway capacity and found that, in many of these cases, reductions in vehicle travel occur, generally confirming that a relationship exists between roadway capacity and vehicle travel. Additional information is provided on this subject in a North American context. The city of Calgary, in Alberta, Canada, is a major urban center with a population of over 850,000 and a downtown employment of over 100,000. Centre Street Bridge is a major road bridge across the Bow River that connects downtown Calgary to the residential area in the northern part of the city. The bridge carries over 34,000 vehicles per day, with heavy peak-period flows. In August 1999, the Centre Street Bridge was closed to car and truck traffic for 14 months for major repairs. A detailed study was undertaken of changes in traffic and in transit and pedestrian flows that took place in weekday travel patterns during the closure. This included both analysis of observed count data before and during the closure and an interview survey with over 1,300 car users of the Centre Street Bridge and the other bridges serving the north side of the downtown. The major findings of this study are summarized here. Particular emphasis is placed on explaining what happened to the vehicle trips that used the bridge before the closure.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".