Bibliographic record
Abstract
Through air inhalation, dust ingestion and dermal exposure, the indoor environment plays an important role in controlling human chemical exposure. Indoor emissions and chemistry can also have direct impacts on the quality of outdoor air. And so, it is important to have a strong fundamental knowledge of the chemical processes that occur in indoor environments. This review article summarizes our understanding of the indoor chemistry field. Using a molecular perspective, it addresses primarily the new advances that have occurred in the past decade or so and upon developments in our understanding of multiphase partitioning and reactions. A primary goal of the article is to contrast indoor chemistry to that which occurs outdoors, which we know to be a strongly gas-phase, oxidant-driven system in which substantial oxidative aging of gases and aerosol particles occurs. By contrast, indoor environments are dark, gas-phase oxidant concentrations are relatively low, and due to air exchange, only short times are available for reactive processing of gaseous and particle constituents. However, important gas-surface partitioning and reactive multiphase chemistry occur in the large surface reservoirs that prevail in all indoor environments. These interactions not only play a crucial role in controlling the composition of indoor surfaces but also the surrounding gases and aerosol particles, thus affecting human chemical exposure. There are rich research opportunities available if the advanced measurement and modeling tools of the outdoor atmospheric chemistry community continue to be brought indoors.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".