Comparação entre dois métodos para determinação da qualidade da água tratada
Bibliographic record
Abstract
The assessment of water quality destined to population consumption is something essential; for this reason the physical, chemical and bacteriological parameters are monitored and must be according to the limits established in legislation. Thus, the present study has determined and compared the application of two Water Quality Indexes (WQI) of 249 treated water samples, collected in the water supply system of the city of Goiania, during a period of 24 months. These samples were subjected to analysis of 10 physical-chemical parameters and 3 microbiological parameters. The WQI values for the samples were determined using a Canadian WQI calculation model, and also by using different calculation model, employed by the local State Company. The results indicated that the water distributed in 88.8% of the samples were rated as excellent by the two models, indicating that the model employed by local State Company is more restrictive than the Canadian model, besides that there is a seasonal influences pointing to a worse water classification in the rainy season. Keywords: WQI, Water quality, Canadian model.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.039 | 0.023 |
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".