Assessment of Health problems and Genetic Damage in Residents of Uppal Industrial Area
Bibliographic record
Abstract
Uppal and Patancheruvu are two important industrial zones in twin cities. Since 1980's many industries such as pharmaceutical drugs, paints, pesticides, steel, plastics, textiles, leather, rubber, etc. were established. Many a time complaints of Industrial Pollution from residents of Uppal industry area were received by the government with a request to kindly take necessary step to prevent industrial pollution in this area. Although very few studies were carried out on people living here and hence an attempt was made to take up a large scale study. Epidemiological, genetic, cytogenetic and molecular studies were carried out in subjects living in Uppal industrial area. For comparison the residents of Ameerpet were selected (control group). 560 people residing in and around Uppal Industrial belt were selected for epidemiological studies and for comparison people living in non-industrial area (Ameerpet) and not exposed to either agricultural or industrial chemicals occupationally were selected (Control group).The results showed an increased frequency of health problems when compared to control group. The prominent health problems were hypertension, diabetes, renal problems, skin problems, gastrointestinal disorders, infections, nervous disorders, muscular pain, respiratory disorders, and weakness/lassitude. Reproductive outcome of 175 couples living in this area was studied. The reproductive outcome was assessed by measuring the incidence of abortions, stillbirths, malformations, prenatal deaths, etc. The results showed a decrease in the fertility (87.33% against 88.88% in control group) and a high incidence of abortions (8.41% against 5.09% in control group). Studies on incidence of chromosomal aberrations and sister chromatid exchanges in 60 people living here were taken up and results shown the increased levels of cytogenetic damage when compared to the controls.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".