Culinary Properties of Raw Versus Conventional Soy Sauce during Tuna Preparation
Bibliographic record
Abstract
Soy sauce is a traditional Japanese seasoning made from fermented soybeans. As global demand grows, identifying novel soy sauce applications and benefits must become a priority. While conventional soy sauce undergoes heat-sterilization, filter-sterilization produces a lighter-colored (raw) soy sauce with preserved mold enzyme activities. As the impact of raw soy sauce during food (especially seafood) preparation remains unstudied, the present study compared the differential impact of raw and conventional soy sauce on tuna culinary properties. First, soy sauce color and protease activity were assessed. Next, tuna was marinated in soy sauce and non-alcoholic mirin for 0, 10, 35, or 60 min. Finally, marinated tuna properties (mass, salt content, surface salt penetration, color, rupture load, surface wetness, and protein content) were objectively assessed, and subjective sensory evaluation (appearance, aroma, wetness, softness, saltiness, umami, and overall taste) was performed by a blinded panel. Findings confirmed the lighter color of and the preservation of protease activity in raw soy sauce. Raw soy sauce significantly enhanced surface tenderization, salt penetration, and wetness, while both soy sauces increased surface firmness via salt-induced dehydration. Respondents significantly preferred the appearance and saltiness level of raw soy sauce-marinated tuna, and the umami and overall taste of tuna marinated in raw soy sauce for 60 min. The findings of this study, to our knowledge, demonstrate for the first time the potential culinary superiority of raw soy sauce in certain applications, and support future research to further define such applications.
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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 | 0.001 | 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) | 0.000 | 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".