Applying the coagulation and reverse osmosis for water recovery from evaporative water
Bibliographic record
Abstract
Abstract Applying the coagulation and reverse osmosis for water recovery from evaporative water. Evaporative water from the concentration of yeast slurry is a potential raw material for water recovery. It is characterized by low pH (4.6-6.3), increased turbidity (3.65-13.7 NTU), and high content of total organic carbon (356-754 mg/L). Its treatment in the volume coagulation process using NaOH and coagulant PIX 111, was studied. Water turbidity was lowered to a value below 1 NTU, but coagulation did not allow for the removal of organic compounds. Coagulation was effective at temperatures of 20 and 40°C. Pretreatment of the feed water for RO included alkalization, coagulation, sedimentation, and 5 μm fine filtration (variant I), as well as single 5 μm fine filtration (variant II as a blank). In variant I the feed with improved properties was achieved. Membrane filtration allowed for effective desalination of evaporative water, 98 and 73% conductivity retention was obtained, depending on the method of the feed pre-treatment. The organic compounds were removed less efficiently, at 94 and 84%, respectively.
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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 | 0.000 | 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 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".