Source Identification of Carbonaceous Aerosols During Winter Months in the Dhaka City
Bibliographic record
Abstract
Air particulate matter samples were collected using Air Metrics samplers from 11 - 17 January and 19 - 27 January, 2012 at Amin Bazar and Farm Gate sites, respectively. The sampling time was from 8 a.m. - 4 p.m. Three samplers were used of which two samplers were for PM2.5 samples, using Teflon and quartz filters and the others for PM10 samples using Teflon filter. Organic and elemental carbons (OC and EC) were measured in PM2.5 samples at both sites. It has been found that the EC concentration at Amin Bazar is higher than in Farm Gate. The contribution of EC may come from diesel, gasoline and coal/wood combustions in the Amin Bazar site. The present OC/EC data were compared with the previous data. It was found that the concentration of EC became higher than those in the previous year. During last couple of years, Government implemented different policies specially in case of motor vehicles to improve the air quality. But due to the use of diesel in quick rental power plants, the air quality start to deteriorate. BC plays an important role to change the climate. Hence, government should think of alternatives to meet the power demand in place of diesel. DOI: http://dx.doi.org/10.3329/jbas.v36i2.12970 Journal of Bangladesh Academy of Sciences, Vol. 36, No. 2, 241-250, 2012
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".