Use of an air-coupled ultrasound technique to assess the mechanical properties of white salted noodle dough and its potential capability in prediction of cooked noodle texture
Bibliographic record
Abstract
In this study, an innovative technique—air-coupled ultrasound—was used to measure the mechanical properties of white salted noodles, in a fast, non-destructive, non-contact way. The ultrasound technique was sensitive to the changes brought about by dough moisture content, work input (either from the mixing or sheeting process), as well as the changes in noodle properties with time. In addition, the cooked noodle texture was assessed by conventional methods: an instrumental method and a trained sensory panel. Noodles were less firm with increased water content, and with prolonged storage time (24 hours). Noodles made with CWRW (Canada Western Red Winter) flour had a comparable firmness as noodles made from high protein content flour (Canada Western Red Spring). Overall, the cooked noodle texture was highly correlated with the dough properties measured with the ultrasound technique. Therefore, this research suggests that air-coupled ultrasound has a promising capability for the prediction of noodle quality.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".