Approach for developing the proposed operational greenhouse gas emissions levels for Part 9 of the National Building Code of Canada
Bibliographic record
Abstract
This paper presents the methodology developed to quantify operational GHG emissions and set performance levels in the proposed updates to be included in the 2025 edition of the National Building Code (pending approval). The GHG requirements build on the reference vs proposed method widely used in energy codes. Reference GHG emission factors were selected and verified using 240 contemporary house archetypes, which utilized natural gas for space and service water heating. From this baseline six performance levels (from A to F) were defined, with A being the most stringent (≥ 90% improvement compared with the target), and F the least stringent (<10% improvement). The results emphasized that the most significant reduction in GHG emissions can be attributed to changes in the electricity grid mix and equipment selection. In locations where average grid emissions factors are less than 100 g CO₂e/kWh, heat pump systems demonstrated the most significant reduction in GHG emissions compared to the reference, and ultimately compliance with higher operational GHG emissions performance levels (A and B).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".