Fuel Consumption and Emissions of Turnpike Doubles in the Canadian Prairie Region
Bibliographic record
Abstract
This research analyzes fuel consumption and emissions of Turnpike double trailer combinations (Turnpikes) on a regional network in the Canadian Prairies. The research: (1) establishes current benchmarks for fuel consumption of Turnpikes and five-axle tractor semitrailers (3-S2s) with van trailers; (2) develops fuel consumption models for these vehicle types; (3) establishes an understanding of current operating characteristics of Turnpikes in the region; and (4) estimates their system-wide effects in terms of fuel consumption and emissions in Manitoba by applying the developed models. Canadian Prairie region-based carriers revealed an increase in Turnpike travel (from 2007-2009) of 44 percent after the twinning of the Trans-Canada Highway between Winnipeg and Regina in 2007 was completed. Turnpikes can save one third of fuel consumed when compared to 3-S2s; have higher fuel consumption in the winter months; and their use in 2009 reduced fuel consumption and CO2 emissions by five percent compared to 3-S2s.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".