Overview of HOMEChem: House Observations of Microbial and Environmental Chemistry
Bibliographic record
Abstract
The House Observations of Microbial and Environmental Chemistry (HOMEChem) study is a collaborative field investigation designed to probe how everyday activities influence the emissions, chemical transformations and removal of trace gases and particles in indoor air. Sequential and layered experiments in a research house included cooking, cleaning, variable occupancy, and window-opening. This paper describes the overall design of HOMEChem and presents preliminary case studies investigating the concentrations of reactive trace gases, aerosol particles, and surface films. Cooking was a large source of VOCs, CO2, NOx, and particles. By number, cooking particles were predominantly in the ultrafine mode. Organic aerosol dominated the submicron mass, and, while variable between meals and throughout the cooking process, was dominated by components of hydrocarbon character and low oxygen content, similar to cooking oil. Air exchange in the house ensured that cooking particles were present for only short periods. During unoccupied background intervals, particle concentrations were lower indoors than outdoors. The cooling coils of the house ventilation system induced cyclic changes in water soluble gases. Even during unoccupied periods, concentrations of many organic trace gases were higher indoors than outdoors, consistent with housing materials being potential sources of these compounds to the outdoor environment. Organic material accumulated on indoor surfaces, and exhibited chemical signatures similar to indoor organic aerosol.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".