Code national de l'énergie pour les bâtiments : Canada : 2025
Bibliographic record
Abstract
The NECB sets technical requirements that address the protection of the environment in the design and construction of new buildings and in subsequent alterations. The 2025 edition of the NECB includes the following updates: - Expansion of the environment objective to address greenhouse gas emissions - Introduction of a harmonized framework that aims to reduce the operational greenhouse gas emissions of buildings, offering provinces and territories a harmonized pathway to reduce emissions over time by choosing the performance level that best suits their needs - Introduction of energy efficiency requirements for the alteration of existing buildings, offering building officials a harmonized framework to enforce code requirements in retrofits - Updated requirements to account for the impact of thermal bridging through the building envelope Introduction of an energy use intensity path for compliance with energy performance tiers, providing builders with an additional option to demonstrate compliance that recognizes the inherent efficiencies of smaller, more compact housing forms - Inclusion of projected climatic data, which anticipates climate trends over the next 50 years, so buildings are better prepared for future climate conditions in Canada
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.030 | 0.015 |
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".