Bibliographic record
Abstract
Human milk provides all the dietary essential fatty acids, linoleic acid (LA; 18:2n-6) and alpha-linolenic acid (18:3n-3), as well as their longer-chain more-unsaturated metabolites, including arachidonic acid (20:4n-6) and DHA (22:6n-3) to support the growth and development of the breast-fed infant. Human milk levels of LA have increased in Westernized nations from mean levels (g/100 g total fatty acids) of 6 to 12-16 over the last century, paralleling the increase in dietary intake of LA-rich vegetable oils. DHA levels (g/100 g total milk fatty acids) vary from 1% and are lowest in countries in which the intake of DHA from fish and other animal tissue lipids is low. The role of DHA in infant nutrition is of particular importance because DHA is accumulated specifically in the membrane lipids of the brain and retina, where it is important to visual and neural function. An important question is the extent to which many human diets that contain low amounts of n-3 fatty acids may compromise human development. The present paper reviews current knowledge on maternal diet and human milk fatty acids, the implications of maternal diet as the only source of essential fatty acids for infant development both before and after birth, and recent studies addressing the maternal intakes and milk DHA levels associated with risk of low infant neural system maturation.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".