Monitoring and Visualization of Tropospheric Ozone in Rural/Semi Rural Sites of Rawalpindi and Islamabad, Pakistan
Bibliographic record
Abstract
Ozone is one of the most pervasive of the global air pollutants, with impacts on human health, food production and the environment. Present research highlights emphasized the main rural agricultural areas of Rawalpindi and Islamabad for their air quality assessment and visualization in order to evaluate and predict the risk areas to facilitate farmers and policy makers to draft critical guidelines for possible threat of ozone concentrations to the agricultural sector of country in the coming years. Model 400E ozone analyzer was used to determine the ozone concentration. Results indicated the seasonal fluctuation in O3 concentration levels. Mean concentration value of O3 in Rawalpindi and Islamabad is 35 ppb. Climatologically parameters also showed significant association with ozone concentration. Comparison of obtained values of ozone with the WHO standards indicates that O3 levels are still lower than standards. This indicates that we still have a time to reconsider our anthropogenic activities to control the O3 precursors to prevent any deleterious effects on agricultural sector.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".