Nutritional labeling and amino acid profile in high protein Chilean dairy products: a new alternative for health and sports
Bibliographic record
Abstract
INTRODUCTION: Introduction: protein is an essential nutrient that can be obtained through different food sources. In recent years, a growing development in the food industry of dairy products with higher protein content has emerged in the national market. Métodos: the present work analyzed the nutritional information, protein content, and amino acid profile of high protein yogurts. Five main brands of high-protein yogurt (PY) were selected, as was a sample of regular yogurt (RY), and one of whey protein isolate (WP), which underwent a proximal analysis and amino acid profile by high-performance liquid chromatography (HPLC). Results: it was observed that the protein content of the analyzed YP ranged between 7.2 and 15.1 g/portion, representing 6.8 % to 11 % of total content, twice the content of YBAT (3,4 %). Regarding carbohydrates and fats, these were found to range between 6.25 and 13.5 g/serving and 0.9 and 5.3 g/serving, respectively. Leucine content of the PY varied between 0.6 and 1.5 g/portion, which was higher than RY (0.3 g/portion) and lower than WP (2.2 g/portion). The sum of essential amino acids was found to be between 3 and 6.9 g/portion in PY, 1.7 g/serving y 8.5 g/serving in WP. Conclusion: these results show that PYs are a good alternative to promote a correct protein intake, similar to proteins for sports use, so their recommendation could be useful to promote consumption in different populations according to their needs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".