Integrating Pressure-Driven Membrane Separation Processes to Improve Eco-Efficiency in Cheese Manufacture: A Preliminary Case Study
Bibliographic record
Abstract
Pressure-driven membrane separation processes are commonly used in cheese milk standardization. Using ultrafiltration (UF) or microfiltration (MF), membrane separation processes make it possible to concentrate the milk proteins and increase the yields of cheese vats. However, the contribution of membrane separation processes to the environmental impact and economical profitability of dairy processes is still unclear. The objective of this study was to evaluate the contribution of membrane separation processes to the eco-efficiency of cheddar cheese production in Québec (Canada) using process simulation. Three scenarios were compared: two included UF or MF at the cheese milk standardization step, and one did not incorporate membrane separation processes. The results showed that even if membrane separation processes make it possible to increase vat yields, they do not improve the eco-efficiency of cheddar cheese processes. However, membrane separation processes may benefit the eco-efficiency of the process more when used for byproduct valorization.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".