In-Situ and Predicted Performance of a Certified Industrial Passive House Building under Future Climate Scenarios
Bibliographic record
Abstract
The Wood Innovation Research Lab was designed as a low energy-use building to facilitate the construction and testing of engineered wood products by the faculty and staff of the Master of Engineering in Integrated Wood Design Program at the University of Northern British Columbia in Prince George, BC, Canada. Constructed using a 533 mm thick-wall and 659 mm flat roof assembly, it received certification as Canada’s first industrial facility built to the International Passive House standard. Temperature and humidity sensors were installed in the north and south exterior wall assemblies to measure long-term hygrothermal performance. Data collected between 2018–2020 shows no record of long-term moisture accumulation within the exterior assemblies. Data collected during this time period was used to validate hygrothermal performance models for the building created using the WUFI® Plus software. Long-term performance models created using future climate data for five cities across Canada under two global warming scenarios shows favorable results, with an increase in average annual temperatures resulting in lower average relative humidity values at the interior face of the exterior sheathing board in the exterior wall assemblies.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| 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".