A System for Predicting Pollutant Transport in the Atmosphere
Bibliographic record
Abstract
Abstract A system has been developed for numerical prediction of concentrations of pollutants in the atmosphere and their transformation with the use of CHIMERE chemical transport model, which takes into account emissions from stationary and mobile sources and accidental emissions. Meteorological fields are forecasted using the regional high-resolution non-hydrostatic atmospheric model WRF-ARW. The system is fully automated and can be used as a tool for receiving operational information in the work of situation and decision-making centers in the cases of industrial, natural, and man-made accidents. The system was tested for a Russian region. The test results show its efficiency, a possibility of using it in operational and research work and in the development of scenarios of emergency situations anywhere in the Russian Federation, which can help to eliminate the consequences of accidents. The first results of atmospheric pollution calculation with the system are described and can be considered as test. To obtain statistically reliable results, it is necessary to have longer series of measurements of atmospheric pollution concentrations with higher resolution.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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".