New Insights into Freeway Capacity at Work Zones: Empirical Case Study
Bibliographic record
Abstract
A construction project in Ontario, Canada, provided the opportunity to use field data to investigate freeway capacity at long-term lane closures due to rehabilitation work. Data from two lane closures at the same construction site (eastbound and westbound) were examined. The site is located on the Gardiner Expressway in the southern part of downtown Toronto. Data were collected during 4 days, totaling around 53 h of congested traffic operations. Results showed significant variation in freeway capacity in the work zones. Despite this variation, average capacity values are reasonably close to the corresponding values provided in the Highway Capacity Manual. Four intervening variables were investigated; all exhibited significant but different effects on freeway work-zone capacity. These variables included temporal variation (which is thought to relate to driver characteristics), grade, day of week, and weather conditions. The results confirmed the pressing need for more extensive field data that will allow better identification of the effect of various control variables on work-zone capacity.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".