High-yield protein recovery from secondary sludge of paper mill effluent and its characterization
Bibliographic record
Abstract
Maximizing recovery and characterization of extractable proteins from secondary paper sludge is essential to explore the potential value from utilization of readily available waste products from pulp and paper mills. A multistep physicochemical recovery process was used, involving optimum alkaline solubilization of protein into an aqueous phase followed by augmented physical disruption of cell membranes. The final precipitation of solubilised protein was carried out using different acidic media. The optimization studies revealed that the best removal of intercellular contents from sludge can be achieved at pH 12; at this level, up to 88% of available protein is solubilised into the aqueous phase. Of all the precipitating agents used, sulphuric acid proved most effective by recovering 90% of disrupted protein. The combined effect of french press and sonication techniques resulted in significant improvement in the overall yield of recovered sludge protein (RSP). The characterization studies showed the presence of common and essential amino acids in RSP in significant quantities; it also showed that the recovery process can significantly reduce or eliminate heavy metals present in the sludge. The molecular weights (MW) of extractable proteins were determined by PAGE, and it was observed that RSP contains both low and high MW fractions.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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 | 0.000 |
| 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) | 0.007 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".