Effect of Taro Starch-Hydrocolloids Mixture as a Functional Ingredient on the Quality of Milk Dessert
Bibliographic record
Abstract
The study was carried out to investigate the effect of taro starch-hydrocolloids mixture on the physical and sensory properties of milk dessert. Four different hydrocolloid i.e. arabic, Carboxymethyl cellulose (CMC), guar and xanthan gums were mixed with taro starch in different concentration and their potential use in milk dessert as functional ingredients were evaluated. Physical and sensory characteristics were found to be considerably improved in different aspects by adding these functional ingredients. Taro starch-arabic gum blend was observed to be an effective additive to produce creamy texture of milk dessert. Syneresis from dessert was noted to be diminished and sensory characteristics were also found to be improved by adding taro starch-guar gum blend. Similarly, taro starch-xanthan gum blend has effectively been stabilized the texture and sensory properties of milk dessert.
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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 | 0.000 | 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) | 0.001 | 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".