Seasonality\nof the Water-Soluble Inorganic Ion Composition\nand Water Uptake Behavior of Urban Grime
Bibliographic record
Abstract
Impervious surfaces, especially in\nurban environments, are coated\nwith a film composed of a complex mixture of substances, referred\nto as urban grime. Despite its ubiquity, the factors that dictate\nurban grime composition are still not well understood. Here, we present\nthe first study of the seasonal variation in composition of water-soluble\ninorganic ions present in urban grime, performed by analyzing samples\ncollected in Toronto for 4-week intervals over the course of a year.\nA clear seasonality in the composition is evident, with NaCl dominating\nin the winter months and Ca<sup>2+</sup> and NO<sub>3</sub><sup>–</sup> dominant in the summer. We compare the grime composition to the\nwater-soluble ion composition of PM<sub>2.5</sub> and PM<sub>10</sub> in order to infer chemistry occurring within the grime and find\nevidence that chemistry occurring within the urban grime matrix could\nprovide a source of ClNO<sub>2</sub> and NH<sub>3</sub> to the urban\natmosphere. The uptake of water by urban grime also shows a clear\nseasonality, which may be driven by the changing proportions of nitrate\nsalts and/or oxidized organic compounds over the year.
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How this classification was reachedexpand
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.113 | 0.004 |
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; both teacher heads agree on what is shown here.
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".