PARTICLE SIZE EFFECT ON SOY PROTEIN ISOLATE EXTRACTION
Bibliographic record
Abstract
This study was undertaken to determine if the yield and purity of soy protein isolates could be improved by changing the particle size of the starting raw material. Soy protein isolates were extracted from hexane defatted soy flour ground to three different average particle sizes (89.5 ± 1.1, 184.2 ± 1.6 and 223.4 ± 6.4 µm). By decreasing the average particle diameter of the starting raw material (soy flour) from 223.4 to 89.5 µm the total solids recovery increased from 23 to 32% (P = 0.00008), while the protein recovery increased from 40 to 52% (P = 0.00004). Final protein content (i.e., purity) of the soy protein isolates was not significantly impacted by average particle size. The results clearly demonstrated that protein recovery can be increased by >30% by decreasing the average particle size of the starting raw material (i.e., defatted soy flour), without having any detrimental impact on the purity of the final soy protein isolate.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".