Supporting Information Condensational Uptake of Semivolatile Organic Compounds in Gasoline Engine Exhaust onto Pre-existing Inorganic Particles
Bibliographic record
Abstract
AURAMS (version 1.4.0) is an off-line chemical transport model (CTM) that is driven by the Canadian operational weather forecast model, GEM (Global Environmental Multiscale model). GEM (version 3.2.2) was used to produce meteorological fields with a 15-km horizontal grid spacing. GEM was run for 12-hr periods from reanalysis files with a 6-hr spin-up and 6-hr of simulation stored for the CTM. AURAMS was run with a 15km horizontal grid spacing for a domain covering the northeastern U.S. and eastern Canada and using climatological chemical boundary conditions. Gridded hourly anthropogenic point, area and on-road mobile emissions files were prepared for the CTM with the 2005 Canadian and 2005 U.S. national criteria-aircontaminant emissions inventories and version 2.2 of the SMOKE emissions processing system. Total gasoline exhaust organic vapour was treated as an additional gas-phase species in the on-road mobile emissions stream of the emissions processing system. This species was emitted, transported, lost by gas-phase chemistry and allowed to reach an equilibrium partitioning with sulphate aerosol based on the effective uptake coefficient fit
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.427 | 0.038 |
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".