Evaluation of Energy Efficiency Measures in High-rise Buildings from a Life Cycle Greenhouse Gas Emissions Perspective
Bibliographic record
Abstract
Due to its significant contribution to greenhouse gas (GHG) emissions, the building industry is taking action to fight climate change, developing measures for reducing the operational emissions of buildings. However, some of these well-intentioned measures can result in higher embodied emissions. Under certain conditions, this increase in embodied emissions can more than offset the reductions achieved during the building operational phase. This thesis evaluates the effectiveness of five passive energy efficiency measures to reduce GHG emissions from a life cycle perspective for high-rise residential buildings in Toronto, Canada. Decreasing the window-to-wall ratio was found to be the most effective measure to reduce total GHG emissions. Increasing the continuous insulation on walls and roofs with GHG intensive materials can increase total emissions. The thesis also compares the embodied GHG emissions of curtain walls and window walls finding no practical difference in embodied GHG emissions between the options studied.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".