GLITEROS enteral formula based on tempeh flour and jicama flour for patients with hyperglycemia
Bibliographic record
Abstract
Critically ill patients are susceptible to hyperglycemia during the treatment in the hospital. This condition could reduce immunity and increase the risk of mortality. The use of commercial diabetes-specific enteral reduces blood glucose level but increase the hospitalization cost due to the long-term period. Therefore, the homemade enteral formula developed using tempeh flour and jicama flour. GLITEROS comes from glycemia, tempeh and Pachyrhizus erosus. Arginine, glycine, and isoflavone contained in tempeh flour could improve insulin secretion. Moreover, inulin in jicama flour could control the increasing of blood glucose levels. The purpose of this study was to analyze the viscosity, macro-nutrient content, food fiber and protein digestibility of GLITEROS enteral formula. GLITEROS made from tempeh flour, jicama flour, soybean oil, skim milk, maltodextrin, and sugar. This study was an experimental design with three groups formula, A1 (1:1), A2 (5:3), A3 (2:3). Variables include viscosity, energy density, energy content, carbohydrates, protein, fat, dietary fiber and protein digestibility each with 3x repetitions in duplicate. The data were analyzed using Kruskal Wallis and One-way ANOVA. A1 formula had the highest carbohydrate (62%), dietary fiber (25.59%), and fat (10.49%) lower than A2 and A3 formula. A2 formula had 0.98 kcal/mL density energy and 984 kcal energy, 11,73 cP lower than A3 and A1 formula. A3 formula had the highest density energy (1.13 kcal/ mL), energy (1132.45 kcal), 36.10 cP viscosity, and protein (14.89%) lower than A1 and A2 formula. A1 formula is the most eligible in viscosity, energy density, energy content and protein of enteral formula for hyperglycemia patient according to American Diabetes Association (ADA), Canadian Diabetes Association (CDA), American Society of Parenteral and Enteral Nutrition (ASPEN) requirements.
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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) | 0.001 | 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".