Bibliographic record
Abstract
Moving goods and services efficiently, effectively, and sustainably within an urbanized environment is challenging. The competing road spaces and the abundant traffic and parking regulations for cars, on-surface transit vehicles, pedestrian and cyclists have made truck movement intricate to maneuver on the busy urban streets and highways. The same challenge applies to the rail and air traffic, since goods movement usually share the same rail line infrastructure and air capacity with the commuters. All of these challenges have been further complicated by the goods movement companies who practise the necessary Just-In-Time delivery in order to service the demanding consumer and manufacturing markets and to compensate for the shortage of distribution centres and other infrastructures within the supply chains of commodities and consumer products. Unfortunately, not too many urban communities in Canada have set priorities to tackle the goods movement challenges. As stated in one of thirteen decision making principles in the TAC's A New Vision for Urban Transportation: #7 Improve the efficiency of the urban goods distribution systems... will be difficult because even basic data are lacking and because of the fragmented and highly competitive nature of the trucking industry.... The lack of attention to a sustainable goods movement solution has resulted in inefficient usage of road capacity due to empty container trips (up to 40% of total truck trips), extra greenhouse gas emission by the truck's diesel engine (15 times more than car gas emissions2), and impacting the economy from the perspective of congestion costs (up to $2.7 billion/year to the Greater Toronto and Hamilton Area (GTHA)). Peel Region, one of six regional municipalities in GTHA in Ontario, recognized the challenges and have faced them head on. In collaboration with all levels of government and businesses, Peel Region established the Goods Movement Strategic Plan with 23 Action Items. Among them, Peel Regional Council approved the Freight Transportation Demand Management Study (FTDMS) in 2013 which recommends 11 explicit improvements using Transportation Demand Management (TDM) principles. This project was nominated for the TAC 2015 Sustainable Urban Transportation Award.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".