Avena (Avena sativa) instantánea con trozos de manzana (Pyrus malus) deshidratada
Bibliographic record
Abstract
A change in consumer eating habits has caused an increase in the exportation of breakfast cereals in countries such as Germany, United Kingdom, France, United States and Canada. Breakfast cereals are classified as flakes, puffed grains, integral (high fiber), muesli, cereal bars, and oatmeal. The product belongs to oatmeal classification since flakes are part of the ingredients. The objective of this thesis was to develop an‘instant oatmeal’ that included a mixture of flakes, flour and toasted oat, with dried apple pieces and cinnamon. A completely randomized design was used with 5 treatment products where the oat presentation differed in different proportions and three response variables: water solubility index, water absorption index and swelling power. With an analysis of variance (ANOVA) and Duncan’s mean test with 5% of probability, it was concluded that the treatment 2, which included dried apple pieces, cinnamon and 50% of oat flour, 25% of toasted oat and 25% of flakes, was superior. There were then two focus groups conducted. In the first one the initial formulation was discussed; the second one determined the suitable time (30 seconds) for the mixing of the product with milk before consuming it. This treatment was then submitted to a sensory analysis test in which the group considered 3 attributes: aroma, flavor and appearance, using a hedonic scale of 9 points. The results were then analyzed using mean responses. The mean responses were located between “Like moderately” and “Like slightly” for appearance, and for aroma and flavor, both falling between “Like a lot” and “Like moderately”. In conclusion the product had a great acceptation by consumers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".