Healthy food design and early childhood nutrition: Nutritional and food safety assessment of fermented and malted multi-grains instant weaning porridge fortified with defatted pumpkin (Cucurbita pepo) seed flour
Bibliographic record
Abstract
Poor-quality diets are one of the most significant barriers to children's survival, growth, development, and learning today. In the context of this experiment, weaning porridge from complementary flour blends of locally available foodstuffs (millet, sorghum, green beans, and pumpkin seeds) was formulated for nutritional, functional, microbiological, and sensory acceptability. The results outlined that all the developed weaning porridge complied with the energy and nutrient density (zinc, iron, and protein) criteria. Energy (2.06-2.08 Kcal/g), protein (4.09-5.44% g/100 Kcal), iron (3.96-4.59 mg/100 Kcal), and calcium (0.39-1.37 mg/100 Kcal) were the nutrient density values identified. The functional features revealed an excellent reconstitution index (5.25-4.53) with a significant difference (P<0.05), a swelling index ranging from 1.03% to 0.57%, and a viscosity ranging from 195.5 cp to 204.5 cp. This study provides valuable insight that complementary foods made from locally available foods are potential solutions for mitigating childhood malnutrition and providing adequate complementation to breastfeeding in resource-poor and technologically underdeveloped countries by providing the needed energy and nutrient densities for immunity, well-being, growth, and development of young children and infants without fortification.
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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 | 0.001 | 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".