Prediction of maximum permeate flux (%) of disc membrane using response surface methodology (RSM)
Bibliographic record
Abstract
The paper investigates increasing permeate flux (%) of the disc membrane which can improve the quality of rubber industrial effluent of Tripura. Response surface methodology was used to optimize the independent influencing parameters to improve the permeate flux. The effect of different influencing parameters like operating pressure, membrane pore size, and inlet feed velocity on membrane permeate flux were studied to determine the optimum operating conditions within the predefined boundary. The experiments were pre-planned and designed according to central composite rotatable design, and second-order polynomial regression model was developed for regression and analysis of variance study. Results show the membrane has maximum permeate flux (%) when the operating pressure is 14.50 Pa, pore size is 0.20 μm, and inlet feed velocity is 2.10 m/s. The Pareto analysis in the study established that the inlet velocity was the most influential parameter in the model equation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".