Analyzing the Performance Gaps in Passive House Retrofit and New Construction Multi-Unit Residential Buildings
Bibliographic record
Abstract
Ensuring buildings operate as designed is critical to achieving performance goals related to energy and carbon emissions as well as health and comfort. This thesis examines energy and ventilation performance in multi-unit residential buildings (MURBs) constructed to Passive House and EnerPHit standards in Hamilton, Ontario. Discrepancies in energy performance arise from design assumptions, occupant behavior, and weather conditions. To address these, recommendations are made about proactive design strategies and ensuring mechanical system specifications are adhered to during construction. Ventilation performance deviations highlight the ongoing necessity for post-occupancy monitoring and regular recommissioning. This is recommended to ensure that the building performance adheres to the established certification (e.g. Passive House). In conclusion, the study offers valuable insights for future MURB projects, emphasizing the pivotal role of research team involvement in the design phase and continuous verification of system performance to identify and learn from the energy and ventilation performance gaps.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".