Correlations between the internal diffusion and equilibrium partition coefficients of volatile organic compounds (VOCs) in building materials and the VOC properties
Bibliographic record
Abstract
In this study. a novel experimental method that was previously developed was used to directly measure the internal diffusion (D) and the equilibrium partition coefficients (ke for three classes of volatile organic compound (VOC), (1) aliphatic hydrocarbons, (2) aromatic hydrocarbons, and (3) aliphatic aldehydes, through typical dry building materials (plywood, particleboard, vinyl floor tile, gypsum board, subfloor tile, and OSB). For each chemical class, correlationsbetween D and the VOC molecular weight and between ke and the vapor pressure of VOCs were developed for every product. These correlations can be used to estimate D and ke whendirect measurement data are not available and, thus, facilitate the prediction of VOC emissions from the building materials using mass transfer theory. It was found that the values of diffusioncoefficients for a given material are inversely proportional to the molecular weights of the VOCs, and the values of the partition coefficients are also inversely proportional to the vapor pressures of the VOCs. The measured diffusion and partition coefficients are useful for predicting the emission rates of VOCs from building materials.
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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 | 0.001 | 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 | 0.000 | 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".