Rheological properties of instant fried noodle dough as affected by some ingredients
Bibliographic record
Abstract
Abstract An experiment was set up to investigate the influence of ingredients such as moisture, gum and starch on the rheological properties of instant fried noodle dough. The noodle dough was formulated using a mixture of wheat flour (100%), 0–0.3% guar gum, 0–7.5% starch and 30–42% moisture. The rheological properties of noodle dough were influenced by the ingredients and their interactions. Increasing moisture content decreased Young's modulus ( E ) of dough samples. Addition of gum to dough at a lower moisture content of 30% increased E , decreased the energy at break ( EB ) and increased the storage modulus ( G ′) values. Interactions of starch and gum influenced changes in the rheological parameters at higher moisture contents. Increasing starch content in noodle dough with a lower gum concentration increased EB to a point beyond which further increase in starch concentration decreased EB . Gum and starch improved the binding and mechanical network in the dough. Insufficient water in the dough apparently reduced cohesion in the dough whereas excess water reduced the functionality of gum and starch. Copyright © 2005 Society of Chemical Industry
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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".