Science surrounding the safe use of bioactive ingredients in infant formula: federal comment
Bibliographic record
Abstract
Human milk research has revealed a complex and dynamic biological system within human milk 1 , 2 , 3 . This has illuminated the possibility that biologically active (bioactive) constituents that mimic those found in human milk could be added to infant formula as new ingredients to improve child health. Although human milk is recommended as the sole source of nutrition for infants up to about 6 months of age, only about 25% of infants in the U.S. meet this objective of exclusive breastfeeding 4 , making access to a safe and effective source of nutrition provided by infant formula critical for child health. Although research on the function of these constituents is ongoing, the U.S. Food and Drug Administration (FDA) is tasked with making timely decisions on whether these ingredients can be safely added to infant formula, and if so, at what levels and combinations, and under which conditions, given the existing knowledge base. This challenge led to the partnership between the National Institutes of Health (NIH) and the FDA to host a scientific workshop describing the state of the science on the functional aspects of biologically active human milk components and analogs that could impact safety decisions.
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 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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.006 |
| 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) | 0.000 | 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".