An Acceptability Trial of Desiccated Beef Liver and Meat Powder as Potential Fortifiers of Complementary Diets of Young Children in Indonesia
Bibliographic record
Abstract
The addition of desiccated beef liver to infant and young child complementary foods can be used to overcome nutrient deficits, however its acceptability is unknown. We conducted a series of studies to test the acceptability of complementary foods fortified with either powdered beef liver, beef meat, beef liver + meat or placebo among 96 Indonesian children aged 12 to 23 mo. This was achieved by determining liking of a single test food with added study powder, followed by a 2-wk home trial and focus group discussions to assess liking during repeated consumption of the study powders added to daily meals. The test food with added beef powders were well liked by mothers, with liking scores never falling below neutral on a 7-point scale. After home use, mothers reported that their children moderately liked their meals with added powder, with scores ranging between 3.3 and 3.5 on a 5-point scale. With the exception of lower liking for the combination beef liver + meat powder, there were no detectable differences in mothers' overall perception of child's liking between the placebo and any of the study powders. The low disappearance rate of the study powders during the home trial was a concern, with mothers reporting a strong smell and fishy odor as the major reason why children did not like their meals. Nonetheless, mothers declared they would continue using the powder on account of the nutritional value and perceived health benefits. Strategies are underway to minimize the level of fishy odor in the beef liver powder.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".