Modeling the Impacts of Off-Peak Delivery in the Greater Toronto and Hamilton Area
Bibliographic record
Abstract
Off-peak-hour delivery (OPHD) has the potential to reduce congestion in busy urban areas and at the same time improve the efficiency of logistics providers, shippers, and receivers. There has been growing interest in OPHD in the Greater Toronto and Hamilton Area (GTHA), an important freight hub in Canada. The Government of Ontario is considering permanently relaxing noise by-laws to promote OPHD throughout the province. The purpose of this study is to provide quantitative assessments of the impacts of region-wide adoption of OPHD for the GTHA. A recently developed commercial vehicle (CV) model for the GTHA is presented in the paper. Various OPHD scenarios have been tested with the CV model. The impacts of induced passenger demand have also been demonstrated. Modeling outcomes indicate that OPHD could result in 5,530 vehicle-hours saved in a day after induced demand is accounted for. Light truck carriers would benefit the most by shifting to off-peak hours and prioritizing Toronto and Peel Region customers would yield the highest travel time savings during the off-peak hours.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".