Effect of Various Seasonings on Protease Activity in Raw Soy Sauce
Bibliographic record
Abstract
Raw soy sauce, which is not sterilized, has a bright color and mild aroma, and possesses residual enzymatic activity to break down proteins and starch. Raw soy sauce is often used in combination with other seasonings. The enzymatic activity in raw soy sauce may be affected by the type of seasonings used in combination. In the present study, we examined the effect of cooking with other seasonings on the enzyme activity in raw soy sauce in a model experiment simulating actual cooking. In addition to raw soy sauce, we used white sugar, mirin (hon mirin, mirin-style seasoning, and boiled-down hon mirin), cooking sake, and grain vinegar as seasonings. Protease activity was measured under several heating conditions. When heated at 60°C, the degree of enzyme inactivation decreased as the ratio of the combination of white sugar, mirin-style seasoning, and boiled-down hon mirin increased. The results of the present study suggest that carbohydrate compounds commonly contained in each seasoning have a protective effect on the enzymes in raw soy sauce.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".