The Effectiveness of Roofing Cool Coatings on the Building Energy Demand in a Cold Climate
Bibliographic record
Abstract
An average temperature increase of 2oC over the last 140 years in Toronto may not seem significant, but in reality heating demand for buildings will go down by impacting natural gas usage while cooling demand will go up by impacting electricity-usage. For preparedness against hot summer in cold climate, passive cooling needs to be adopted for building energy efficiency. In warm climate, cool roof technology proves effectiveness in reducing cooling energy demand of buildings but its use in cold climate is not much seen. Thus it is interesting to investigate the effectiveness of cool roofs in cold climate. This study investigates the properties of cool coatings available in North America, their performance on aging and energy saving benefits. The first phase of research includes selection of building, collection of information, field measurement of surface temperatures of the studied building and also lab testing of collected samples. The second phase includes energy modelling of the studied building with validation to understand their energy saving benefits. Finally the most effective cool coating for the studied building is recommended.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".