INVESTIGATION OF EMPIRICAL AND FUNDAMENTAL SOBA NOODLE TEXTURE PARAMETERS PREPARED WITH TARTARY, GREEN TESTA AND COMMON BUCKWHEAT
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT Soba noodles were prepared from brown tartary, green testa and two common buckwheat variety flours with Canada Western Red Spring flour (13.0% protein) and a lower protein (11.5%), but stronger dough strength, Canada Prairie Spring Red (CPSR) flour. Empirical, fundamental and the new Elastic Index (EI) parameter all demonstrated that the lower protein, stronger gluten CPSR variety 5701, yielded superior textural attributes. Tartary buckwheat flour noodle blends' empirical texture results (maximum cutting stress, resistance to compression and recovery) indicated they produced soba noodles with superior texture than the other buckwheat flours because of the lower level of dietary fiber, elevated starch content and lower cooking water uptake. Fundamental tests, such as stress relaxation percent at 20 s, extent of relaxation (K2), loading work and unloading work of tartary buckwheat noodles showed significant differences from the other buckwheat noodles. Among soba noodles, tartary buckwheat noodles had significantly greater ( P < 0.05) elastic‐like properties (higher K2 and EI). The EI parameter was significantly correlated ( P < 0.005) with all empirical and fundamental rheological parameters. PRACTICAL APPLICATIONS Whereas noodle manufacturers prefer local sensory panels to evaluate the texture characteristics of new noodle products, such evaluations provide little insight into the underlying reasons for the panelist preferences. Traditional empirical mechanical tests – maximum cutting stress, recovery and resistance to compression – have not proven to offer the level of discernment required by the industry. Fundamental mechanical properties offer the ability to provide improved discrimination, as well as an understanding of the role of the biochemical components in addressing the noodle's texture.
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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 it