The Potential Adverse Health Effects of Residents Near Hazardous Municipal Solid Waste Dump Site - At Jawahar Nagar- Hyderabad
Bibliographic record
Abstract
In this research paper the Survey has been conducted among 45 residents around the main dumping site of the municipal corporation viz Jawahar Nagar. In this survey it was found that 55% of the people are suffering with respiratory and 45% answered that they not suffering from the respiratory diseases. Twenty five percent of the People suffering from Cough, twenty percent with Bronchitis, twenty percent with Asthma, fifteen percent with Sneezing, ten percent with Suffocation and the rest of the people suffering with other diseases. All the sample householders had different kinds of eye diseases. It was noted that 20% of households had reddening of eye, 65% of households had tearing of eye, 5% of the householders suffered from difficulty in vision and 10% of households were affected by conjunctivitis. The high occurrence of eye diseases in the area might be due to recurrence of fire and gas emissions from the dumping site. During the survey, it was observed that the people around the dump site was suffering from various water borne diseases such as Cholera, Dysentry, Typhoid, Jaundice, Diarrhea etc. Nearly 25% of the people suffering from cholera, 25% from Diarrhea, 20% from Jaundice, 15% from typhoid, 10% from Dysentry etc. It was found that 25% had Cholera, 20% had Jaundice; 25% had Diarrhea; 10% had Dysentery; 15% had Typhoid and 5% had other Diseases
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".