Investigation of a Small‐Scale Asymmetric Centrifugal Mixer for the Evaluation of Asian Noodles
Bibliographic record
Abstract
ABSTRACT A high throughput centrifugal mixer capable of using smaller amounts of flour (50 g) was evaluated for the production of oriental alkaline noodles. The unit requires a small footprint on a laboratory bench and offers variable speed mixing (300–3,500 rpm) for 5–60 sec. Three different mixing bowls, plain, pin, and paddle, were evaluated for the small‐scale production of alkaline noodles using straight‐grade flour derived from Canada Western Red Spring (CWRS) and Canada Prairie White Spring (CPSW) wheat. Under optimized mixing conditions (3,000 rpm for 30 sec), the pin and paddle bowls produced noodle dough with crumb size distribution and adhesion characteristics consistent with commercial requirements. The plain bowl produced dough with larger undesirable dough chunks and showed excessive heat buildup. Noodle sheets produced from this dough were not comparable in color characteristics to conventionally produced noodle sheets. Noodles prepared using the paddle mixer also displayed some significantly different color and texture characteristics than conventionally prepared noodles. However, raw noodle sheets or cooked noodles of either wheat class, prepared using the pin bowl mixer, displayed color values ( L *, a *, and b *) at 2 and 24 hr and cooked noodle texture characteristics (bite, chewiness, resistance to compression, and recovery) comparable to a conventional laboratory‐scale Hobart type mixer. In addition to the very short mixing time and small equipment footprint for the centrifuge mixer, rapid throughput is enhanced by the ability to rapidly clean or interchange bowls and to potentially vary sample size to as little as 5 g. These attributes should be particularly useful in earlier generation breeder programs where large numbers of samples require rapid screening.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".