TRANSPORTATION AND CLIMATE CHANGE MITIGATION: CANADIAN PERSPECTIVES. IN: WEATHER AND TRANSPORTATION IN CANADA
Bibliographic record
Abstract
This paper seeks to establish the role of the transportation sector as a contributor to greenhouse gas (GHG) emissions, critically evaluate Canada's policy response to the Kyoto Protocol, and explore GHG mitigation options within this response. The investigation suggests that Canada has not responded quickly to the challenge of reducing GHG emissions in the transportation sector. A broad spectrum of options have been established that could be used to meet Kyoto reduction targets, but the implementation strategy has not yet been decided. Any significant reduction in GHG emissions will require an approach that combines both technological and behavioral strategies. From a technological standpoint, the greatest potential rests with continued improvements in fuel efficiency of automobiles and diesel trucks. From a behavioral standpoint, the most promising measures rely on price or market mechanisms rather than voluntary change.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.009 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.001 |
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".