O consumo de água in natura em área de ocupação irregular, em zona costeira : estudo de caso da Vila Nova, Matinhos, Litoral do Paraná
Bibliographic record
Abstract
In the city of Matinhos, the coast of Paraná, the network coverage of water supply reaches 100% of the population of the urban area, regularly occupied. However, there are indications that some families are not consuming drinking water standards required by the Health Ministry, even though the water distribution network available in your residence. Part of these families live in irregular settlements called Vila Nova, located in the district board, bathhouse of Caiobá. The occupation took place in the 90s by people seeking job opportunities in the region, both in construction and in general services. Therefore, the occupation is already consolidated. The population is basically fixed by locals and few vacation residences and although the area is still not officially regulated, ie, lots have not been actually documented names of households, there is public infrastructure of water services, to a street lamp and floor. But still, does not have the sewage disposal system, which is dumped in the few existing storm sewer or directly into rivers and canals in the region. The preliminary study data came from the company's regularization Newfoundland and the utility provider of sanitation services in the municipality. The data showed that many households were not being supplied with public water, indicating that these families could be consuming water and raw water sources without treatment, located around. With this data, the study continued with the following: (a) collecting information in the field of environmental diagnosis, (b) collection and analysis of water from two sources and 10 residences in random sampling, consuming water directly from these sources, and (c) secondary data collection by the Municipal Health Matinhos. In the field of sanitation we used data of enrollment water concessionaire and the microbiological analysis of water consumed raw. In health indicators were used incidence of intestinal parasitic diseases such as diarrhea and gastroenteritis, considered important in the evaluation of interventions in sanitation. The methodology considered the environmental study with georeferenced map of sources and residences supplied by these sources. The diagnosis showed that the socioeconomic and environmental greatly compromised. The results showed that all samples were contaminated water. However, according to data from epidemiological sector of the city, there is no relevant content of waterborne diseases such as diarrhea and gastroenteritis in the region.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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; both teacher heads agree on what is shown here.
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".