Toronto's Plan for 100% Renewable Energy by 2067
Bibliographic record
Abstract
The purpose of this major paper is to help the City of Toronto transition to 100% renewable energy. Some of the most salient barriers to achieve that climate security goal are: the limited experience with renewables in the current electrical grid; the aging and crumbling energy infrastructure; and the limited energy conservation ethos amongst local residents, businesses, and industries. Understanding the current state of renewables in the world and Canada makes setting goals and a realistic timeline easier. By summarizing what other cities from around the world did to help their quest towards only renewable energy, lessons and policies were discovered that would benefit Toronto. Three major areas, city policies, buildings, and transportation, were identified to be areas of concentration to help the goal become a reality. The proposed timeline incorporates these areas with realistic dates in which each task should be completed by. The conclusion is that Toronto can reach the goal of becoming 100% renewable energy if the steps are taken and acted upon accordingly. My research indicates that to achieve its climate security targets Toronto needs to start planning immediately a strategy for 100% renewable energy to ensure maximum benefits at the lowest cost to all stakeholders.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.095 | 0.023 |
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".