Gluten-Free Crackers Preparation
Bibliographic record
Abstract
The present work was carried out to prepare gluten free crackers of high quality for celiac ailment patients. Gluten free crackers prepared from rice flour, lentil flour and quinoa flour is an innovative and highly nutritious snacks produce. The chemical analyzed included as minerals and amino acids of broken rice, lentil and quinoa flour and its blends was estimated. Then, chemical composition for gluten free crackers blends was estimated and the results presented that ash, crude protein, fat and fiber contents were higher in all blends prepared using rice flour, quinoa flour and lentil flour than that blend prepared using rice flour. All sensory parameters of free gluten crackers samples B2, B3, B4 and B5 prepared using rice flour, lentil flour, and quinoa flour were somewhat higher than crackers prepared from rice flour B1. Hardness decreased from 74.97 newton in blend (1) made from 100% rice flour to 35.19 newton in blend (5) made from 50% rice flour, 25% lentil flour and 25% quinoa flour. Finally, it could make some bakery products using raw materials free of gluten like rice flour, lentil flour and quinoa flour with high quality that are suitable for celiac ailment patients.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".