Search of Optimum Reduced Salt Cooking Condition on Nikujyaga by Vacuum Cooking Using Random Centroid Optimization.
Bibliographic record
Abstract
真空調理による肉じゃがの最適減塩調理条件をランダム・セントロイド法 (RCO法) を用いて最少実験回数で決定することを試みた.肉じゃがは, プラスチック袋に一定量の野菜 (ジャガイモ, タマネギニンジン) と牛肉及び調味液を入れ, 真空包装し, スチームコンベクションオーブンを用いて100℃で加熱した. まず, 一般的配合の調味料を用いて20, 30, 40分加熱し, 官能検査 (順位法) で最も好まれる調理時間を調べた. その結果は40分であった.次に, 加熱時間40分, 加熱温度100℃, 風味調味料重量を一定 (1.2g) として醤油重量 (0～19.5g) 及び砂糖重量 (0～8.4g) の2つを要因としてRCOプログラムによって示された条件で調理を行い, 官能検査の総合評価が最も高くなる条件を求めた. この場合, 醤油重量16.6g, 砂糖重量4.2gが最適条件で, 普通調理品 (一般的配合の調味料で約20分間鍋で煮たもの) と比べ約33%の減塩効果があった. また, 官能検査の総合評価は, 普通調理品肉じゃがと比べほとんど差がなかったさらに, 醤油重量 (0～16.6g), 砂糖重量 (0～8.4g), 風味調味料重量 (0～3.0g) の3つを要因としてRCOプログラムで同様に調理条件を求めた. その結果, 醤油重量13.4g, 砂糖重量5.5g, 風味調味料重量1.7gが最適条件であった. この時は普通調理品と比べ38%の減塩効果があった. この場合の官能検査の総合評価も普通調理品肉じゃがと比べほとんど差がなかった.
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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 | 0.000 | 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) | 0.000 | 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".