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Record W1500298439 · doi:10.1159/000106370

Whole Cow’s Milk: Why, What and When?

2007· review· en· W1500298439 on OpenAlexaboutno aff
Kim F. Michaelsen, Camilla Hoppe, Lotte Lauritzen, Christian Mølgaard

Bibliographic record

Venuenot available
Typereview
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsnot available
Fundersnot available
KeywordsCow milkPolyunsaturated fatty acidDocosahexaenoic acidFood scienceMedicinePopulationObesityAnimal scienceEnvironmental healthFatty acidBiologyEndocrinology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.002

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.

Opus teacher head0.134
GPT teacher head0.429
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations28
Published2007
Admission routes1
Has abstractyes

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