Exploring the Indoor Air Quality in the context of changing climate in a naturally ventilated residential Building using CONTAM
Bibliographic record
Abstract
Indoor Air Quality (IAQ) of residential buildings is a crucial field of study as it aims important subjects: providing healthy indoor air to inhabitants, avoiding high pollutants concentration and impacts of extreme heat events along with climate change and global warming concerns. In order to set up a performance-based method, a critical question has to be answered: What are the relevant IAQ performance parameters that are mostly affected in the context of climate change? To address this, a measurement campaign was carried out in summer of 2021 at south of Belgium. Indoor temperature, relative humidity, CO, Particulate Matters (PM2.5, PM10), Volatile Organic Compounds (VOCs), NO, NO2 and O3 concentrations were measured with fabricated monitoring devices of low-cost sensors, as well as the corresponding outdoor values. In the first step of this study, IAQ parameters are computed using designed model with CONTAM software for the test house. In the next step, the validation of the developed model is investigated.
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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) | 0.001 | 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".