www.elsevier.com/locate/trd Greenhouse gas emissions and the surface transport of freight in Canada
Bibliographic record
Abstract
Under the Kyoto Protocol, Canada has committed to an average annual reduction of greenhouse gases of 6 % below 1990 levels between 2008 and 2012. The transportation of freight contributes to 9 % of Canada’s emissions. Through the application of decomposition techniques and scenario explorations, we show that since 1990, increasing cross-border trade and a concurrent modal shift towards trucks were the most important determinants in increasing freight sector emissions. Looking toward 2012, a number of new developments are occurring. Trade with Asia is rising rapidly with rail appearing to be rising proportionally as a transportation mode. Federal government initiatives on the US and Canadian sides of the border are stimulating advanced technology, while higher fuel prices are increasing freight rates and encouraging carriers to seek efficiency gains. Based upon the most likely progression of these factors, emissions will rise a further 10 % by 2012 and thereby push the sector to be 35 % above base year values.
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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 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 0.003 |
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".