Emerging investigator series: chemical and physical properties of organic mixtures on indoor surfaces during HOMEChem
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Organic films on indoor surfaces serve as a medium for reactions and for partitioning of semi-volatile organic compounds and thus play an important role in indoor chemistry. However, the chemical and physical properties of these films are poorly characterized. Here, we investigate the chemical composition of an organic film collected during the HOMEChem campaign, over three cumulative weeks in the kitchen, using both Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR MS) and offline Aerosol Mass Spectrometry (AMS). We also characterize the viscosity of this film using a model based on molecular formulas as well as poke-flow measurements. We find that the film contains organic material similar to cooking organic aerosol (COA) measured during the campaign using on-line AMS. However, the average molecular formula observed using FT-ICR MS is ∼C50H90O11, which is larger and more oxidized than fresh COA. Solvent extracted film material is a low viscous semisolid, with a measured viscosity <104 Pa s. This is much lower than the viscosity model predicts, which is parametrized with atmospherically relevant organic molecules, but sensitivity tests demonstrate that including unsaturation can explain the differences. The presence of unsaturation is supported by reactions of film material with ozone. In contrast to the solvent extract, manually removed material appears to be highly viscous, highlighting the need for continued work understanding both viscosity measurements as well as parameterizations for modeled viscosity of indoor organic films.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it