Effect of Conductivity Control on the Separation of Whey Proteins by Bipolar Membrane Electroacidification
Bibliographic record
Abstract
Since the limiting factor of the bipolar membrane electroacidification (BMEA) process at 20% WPI (whey protein isolate) was hypothesized to be the lack of mobile ion inherent to the protein solution at pH 5.0, the aim of the present work is to study the effect of the conductivity control on the precipitation behavior of whey protein. BMEA performances were evaluated by measuring electrodialytic parameters, protein kinetic precipitation, molecular profiles, and isolate chemical composition and purity. The highest protein precipitation with 10% WPI solution was obtained at pH 4.6 and at a conductivity level of 200 microS/cm maintained with many 0.4-mL additions of 1.0 M KCl (200 microS[+]), with a 46% precipitation of the total protein, beta-lg composing the main part of the precipitated protein. With a 20% WPI solution, it was possible to reach pH 4.65 with conductivity control at 350 microS/cm. However, the 27% protein precipitation was still low. The changes in viscosity as pH decreases observed at 20% WPI would decreased the final precipitation rate of beta-lg, since the viscosity of the 20% WPI dispersion was very different.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".