Bibliographic record
Abstract
Abstract To support the growth and development of the breast‐fed infant, human milk provides the dietary essential fatty acids, linoleic acid (LA; 18:2n‐6), α‐linolenic acid (ALA, 18:3n‐3), as well as longer‐chain polyunsaturated fatty acids including arachidonic acid (20:4n‐6) and docosahexanoic (DHA 22:6n‐3). The linoleic acid, alpha‐linolenic acid, DHA and arachidonic acid concentration of pasteurized and unpasteurized human milk remains stable during the first month of storage at –20°C and –80°C. However after the first month, a slow decrease in concentration progresses until the end of 6 months of storage at both temperatures. The levels of n‐6 and n‐3 fatty acids, particularly linoleic acid, alpha‐linolenic acid and DHA, in human milk vary widely within and among different populations, and are readily changed by maternal dietary intake of the respective fatty acid. The present paper reviews recent understanding from key researchers of maternal diet and human milk fat composition and form our work the effect of milk fat composition on storage conditions. It is important to understand that maternal diet can affect human milk fat composition and subsequently infant development and growth.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".