A Study of Factors Affecting in Increasing or Decreasing of Radon Levels in Buildings of Suwaylih Town
Bibliographic record
Abstract
This research aimed to study the factors affected in radon levels in buildings of Suwaylih town (altitude about 900 to 1300 above the sea level) as areference to Jordan. The study was started from august, 10, 2012 to October, 10, 2012. Suwaylih Town divided into six districts namely, Al-Kamaliah, Al-Rahmaniah, Al-Sharqy, Al-Fadielah, Maysaloon, Al-Bashaaer districts. About 780 Passive dosimeters containing highly pure CR - 39 were distributed randomly in districts of Suwaylih town. The indoor dosimeters were collected after three months. The collected detectors were chemically etched using 30% KOH for 9 hours at 70 ± 0.1 °C. An optical microscope was used to measure the nuclear alpha track density on the detectors surfaces. The research results showed that radon concentration affected by many factors, for example, the average concentration in guest rooms was 83 ± 18 Bq.m-3 and 70 ± 14 Bq.m-3 in bed rooms, while it was 53 ± 10 Bq.m-3 in living rooms. Morever, the concentration was about 97 ± 15 Bq.m-3 in rooms without ventilation while the concentration was about 30 ± 10 Bq.m-3 at rooms ventilated more than 9 hours daily. The study also showed the concentration was relatively high 90 ± 18 Bq.m-3 in buildings made of stones while concentration was low 47 ± 12 Bq.m-3 in the buildings made from blocks. In addition, the concentration was different with increase in age of building, the average were 63 ± 15 Bq.m-3, 51 ± 13 Bq.m-3 and 39 ± 11 Bq.m-3 in more than 25 years, between 10 - 25 years and less than 10 years, respectively. In general the radon concentration in Suwaylih town was found to be about 62 ± 13 Bq.m-3.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".