Environmental benefits of plug-in hybrid electric vehicles: The case of Alberta
Bibliographic record
Abstract
Plug-in Hybrid Electric Vehicles (PHEVs) are emerging as a promising alternative for the existing transportation system. This technology is envisioned to run on electricity from the grid, stored in high capacity batteries, for short trips and switch to a conventional fuels for long trips. Thus, the demand for electricity will significantly grow if this technology is adopted widely. Although, PHEV technology is generally considered to be more environmentally friendly than conventional transportation systems, especially in regions with a diverse electric power generation fleet, the environmental impacts of such wide integration of PHEVs need to be investigated in thermal-dominated systems, such as Alberta's. This paper studies the potential environmental impacts of the wide adoption of PHEVs in the context of Alberta, given the 90% share of thermal units and the growing interstes in wind power developments in the province. Various scenarios are considered for supplying the required energy for PHEVs and the resulting gas consumption and emission reductions are estimated.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".