Radiation Risk Assessment on Public in Motijheel Thana, Dhaka, Bangladesh
Bibliographic record
Abstract
Objective: The pollution free environment is required for healthy life. The real-time radiation monitoring is very important for radiation hazard detection in the environment. The excess life-time cancer risk (ELCR) on public is to assess based on the real-time radiation monitoring data in the area. Methods: The real-time radiation monitoring was performed using portable digital radiation monitoring device. This real-time digital portable radiation monitoring device meets all European CE standards as well as the American “FCC 15 standard”. The real-time digital portable radiation monitoring device was placed at 1 meter above the ground on tripod and data collection time for each monitoring point (MP) was 1 hour. 27 MPs were chosen for collection of real-time radiation data at various outdoor environment in Motijheel Thana, Dhaka from May-August 2018.Results: The real-time radiation dose rates at Motijheel Thana due to natural radionuclides were ranged from 0.095 ± 0.041 µSv.h-1 to 0.185 ± 0.042 µSv.h-1 with an average of 0.147 ± 0.047 µSv.h-1. The annual effective dose to public from outdoor environmental radiation at Motijheel Thana were found to be 0.166 ± 0.066 mSv to 0.324 ± 0.061 mSv with an average of 0.257 ± 0.039 mSv. Excess Life-time Cancer Risk (ELCR) on public are also estimated based on annual effective dose that is ranged from 0.662 ×10-3 to 1.289 ×10-3 with an average value of 1.025 ×10-3, which is higher than world average value of 0.29×10-3. Conclusion: This type of study is required for detection of the radiation hazard arising from the natu-ral as well as man-made sources and also for generation of the baseline database. From this study, it is observed that there is no pose any radiation hazard in the study area due to man-made sources.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".