STATISTICAL ANALYSIS TO IDENTIFY THE MAIN PARAMETERS TO THE WASTEWATER QUALITY INDEX OF CETP : A CASE STUDY AT VAPI, GUJARAT, INDIA
Bibliographic record
Abstract
The Wastewater Quality Index (WWQI) for wastewater of Common Effluent Treatment Plant (CETP) was found considering all the parameters described by Central Pollution Control Board (CPCB). CCME (Canadian Council for Management for Environment) method was used for the development of WWQI. Initially 23 parameters were analysed. But the values of some parameters were very low with respect to their prescribed limits and few parameters were found totally absent during the analysis. Hence, these parameters were omitted and WWQI was developed with 16 parameters. Further, with the help of software called SPSS correlation between WWQI and different parameters of wastewater was found out. From this analysis, the parameters significantly affecting WWQI were determined and a regression equation was developed considering these parameters only using SPSS software. Again, WWQI was found out with the help of regression equation. At the last results from both CCME method and regression equation were compared.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".