Bibliographic record
Abstract
This paper presents an assessment of air quality of the city Győr, located 120 km west to the capital of Hungary.Two urban air monitoring stations are operated by the local Environmental Protection Laboratory in the city.The concentration data of major air pollutants (CO, NOx, SO2, C6H6, O3, PM10, PM2.5), PM10-bound heavy metals (Pb, Cd, As and Ni) and some polycyclic aromatic hydrocarbons (PAHs) including benzo(a)pyrene (BaP), benzo(a)anthracene, sum of three benzofluoranthene (b, k and j) isomers, indeno(1,2,3-cd)pyrene and dibenzo(a,h)anthracene are available for the assessment based on the latest published monitoring data of the Hungarian Air Quality Monitoring Network.The levels of pollutants were compared with the Hungarian and EU limit or target values defined for health protection and the WHO air quality guidelines (AQGs) or estimated reference levels (RLs).Moreover, the air quality index values for the pollutants were calculated.The results indicated that the main pollutants were BaP, PM10 and PM2.5 in the Győr atmosphere.The annual mean concentration of PM10 and PM2.5 aerosols reached the WHO AQGs (20 and 10 µg/m 3 ), while that of the BaP it was about 5.5 times higher than the WHO RL value of 0.12 ng/m 3 .However, a good or excellent air quality was identified for all examined air pollutants based on the concentration data evaluated by the Hungarian and EU limit or target values.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".