Seasonal Variations and Characterization of Solid Aerosols Related to Faisalabad (Pakistan) Environment
Bibliographic record
Abstract
Black solid aerosols were monitored continuously at Faisalabad using Gaussian dispersion model and nucleation model. Data for one year 2006 was analyzed here keeping in view the meteorological and climatological conditions of Faisalabad co-relating them with concentration gradient. Winter has minimum concentration, i.e. equivalent to background level followed by summer (598.80 μmg/m3), Moon Soon (2762.00 μmg/m3) and finally Post Moon Soon (8863.00 mg/m3). Temperature and pressure gradients both were negative co-relationed with black solid aerosols. These results were not in accordance with other studies, the reason may be the complexity of the Faisalabad environment on account of its geographical, geological and industrial setup confirmed by longitudinal, latitudinal effects and mix plume behavior. A positive co-relationship between biomass burning and seasonal variation i.e. low concentration of particulate matter i.e., 637.30 μg/m3 in summer and high in winter such as 3954 μg/m3.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".