Water Quality Assessment of Groundwater Resources in Nagpur Region (India) Based on WQI
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Water quality index (WQI) has been calculated for different groundwater sources i.e . dug wells, bore wells and tube wells at Khaperkheda region, Maharashtra (India). Twenty two different sites were selected in post monsoon, winter and summer season. And water quality index was calculated using water quality index calculator given by National Sanitation Foundation (NSF) information system. The calculated WQI showed fair water quality rating in post monsoon season which then changed to medium in summer and winter seasons for dug wells, but the bore wells and hand pumps showed medium water quality rating in all seasons where the quality was slightly differs in summer and winter season than post monsoon season, so the reasons to import water quality change and measures to be taken up in terms of groundwater quality management are required.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 it