Whole Cow’s Milk: Why, What and When?
Bibliographic record
Abstract
There are differences between at what age industrialized countries recommend that cow's milk can be introduced to infants. Most countries recommend waiting until 12 months of age, but according to recommendations from some countries (e.g. Canada, Sweden and Denmark) cow's milk can be introduced from 9 or 10 months. The main reason for delaying introduction is to prevent iron deficiency as cow's milk is a poor iron source. In one study mainly milk intake above 500 ml/day caused iron deficiency. Cow's milk has a very low content of linoleic acid (LA), but a more favorable LA/alpha-linolenic ratio, which is likely to be the reason why red blood cell docosahexaenoic acid (DHA) levels seem to be more favorable in infants drinking cow's milk compared to infants drinking infant formula that is not supplemented with DHA. It has been suggested that cow's milk intake can affect the later risk of obesity, blood pressure and linear growth, but the evidence is not convincing. There are also considerable differences in recommendations on at what age cow's milk with reduced fat intake can be introduced. The main consideration is that low-fat milk might limit energy intake and thereby growth, but the potential effects on development of early obesity should also be considered. Recommendations about the age for introduction of cow's milk should take into consideration traditions and feeding patterns in the population, especially the intake of iron and long-chain polyunsaturated fatty acids and should also give recommendations on the volume of milk.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".