Investigation of building materials as VOC sources in indoor air
Bibliographic record
Abstract
Source control using low emission building materials followed by ventilation has been considered as one of the most effective strategies for controlling volatile organic compounds (VOCs) indoors. To apply this strategy, it is necessary to have a decision-making tool for assessing the impact of material emissions on indoor air quality under various ventilation conditions. Therefore, a multi-year, client-supported project on material emissions and indoor air quality modelling was launched from 1996 to 2000 to develop such a tool, known as Material Database and Indoor Air Quality Simulation Program (MEDB-IAQ). On the project sponsors' suggestion, a follow-up project (Phase II) was conducted between 2000 and 2004 to improve the MEDB-IAQ. In this project, efforts were made to characterize VOC emissions for a total of 60 building materials and 90 chemicals. The emission data were incorporated into the MEDB-IAQ. Additional tasks were also conducted, including emission model development based on fundamental mass transfer theory and the investigation of environmental factors on material emissions. This paper provides a brief summary of the main tasks undertaken in both phases of the project.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".