The impact of roof morphology on solar potential: making Toronto suburbs solar ready
Bibliographic record
Abstract
Abstract Rapid urbanization, the increasing effects of climate change, the need to reduce fossil fuels’ dependency as well as to improve cities’ resiliency are accelerating the shift towards renewable energy. Additionally, unnecessary complex roof morphologies that are often pushed by suburban divisions’ developers to make houses look more “opulent” and appealing to homebuyers, also impede the smooth integration of active solar technologies. To address this, and to respond to increasing homebuyers’ interest in renewable energy, this study looks to demonstrate how relatively minor design changes could affect the potential for solar generation and create ‘solar ready’ homes without compromising on the aesthetic of the roof morphologies in styles expected by homebuyers. It looked at six different roof morphological forms ranging from small to large houses, a common suburban house archetype in Canada. The roof configurations were remodelled to remove ‘fake dormers’, minimise ridges and valleys, etc. This process helped maximize the south, south-east, south-west, east and west facing surfaces. The results show that these changes could have a significant impact on the magnitude of solar power generation. The power output from a remodelled neighborhood at an optimized orientation exceeded the community’s electricity demand by 24%.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".