Characterization of Polar Organic Compounds in the Organic Film on Indoor and Outdoor Glass Windows
Bibliographic record
Abstract
Organic films on an impervious surface (window glass) were sampled at paired indoor-outdoor sites in July 2000 and characterized for their paraffinic and polar organic compositions along an urban-rural transect. Four classes of polar compounds (C11-C31 aliphatic monocarboxylic, C6-C14 dicarboxylic, nine aromatic polycarboxylic, and five terpenoid acids) constituted between 81 and 95% (w/w) of the total organic fraction analyzed comprising n-alkanes (C10-C36), 46 PAH, 97 PCBs, and 18 OC pesticides. Concentrations of the polar compounds plus their precursors, n-alkanes, ranged from 8 to 124 microg m(-20 and were dominated by monocarboxylic acids (67-89%, w/w). On outdoor windows, n-alkanes, aromatic acids, and terpenoid acids decreased in concentration along the urban-rural transect. The carbon preference index values and the interpretations of individual compounds indicate that the main sources of n-alkanes were plant waxes followed by petrogenic sources; monocarboxylic and dicarboxylic acids were from plant waxes and animal fats. Results of principal component analysis showed closer correspondence between outdoor and indoor signatures than among locations. In outdoor films, these compounds are suggested to play an important role in mediating chemical fate in urban areas by air-film exchange and facilitating "wash-off" due to their surfactant-like properties. In indoor films, these compounds provide a medium for the accumulation of more toxic compounds.
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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 | 0.000 |
| 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".