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Record W2791703342 · doi:10.3390/antiox7020032

Phytochemicals in Human Milk and Their Potential Antioxidative Protection

2018· review· en· W2791703342 on OpenAlexaff
Apollinaire Tsopmo

Bibliographic record

VenueAntioxidants · 2018
Typereview
Languageen
FieldNursing
TopicInfant Nutrition and Health
Canadian institutionsCarleton University
Fundersnot available
KeywordsPhytochemicalOxidative stressHuman healthHealth benefitsFood scienceHuman nutritionMedicineOxidative damageBiotechnologyEnvironmental healthBiologyTraditional medicineBiochemistry

Abstract

fetched live from OpenAlex

Diets contain secondary plant metabolites commonly referred to as phytochemicals. Many of them are believed to impact human health through various mechanisms, including protection against oxidative stress and inflammation, and decreased risks of developing chronic diseases. For mothers and other people, phytochemical intake occurs through the consumption of foods such as fruits, vegetables, and grains. Research has shown that some these phytochemicals are present in the mother's milk and can contribute to its oxidative stability. For infants, human milk (HM) represents the primary and preferred source of nutrition because it is a complete food. Studies have reported that the benefit provided by HM goes beyond basic nutrition. It can, for example, reduce oxidative stress in infants, thereby reducing the risk of lung and intestinal diseases in infants. This paper summarizes the phytochemicals present in HM and their potential contribution to infant health.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.058
GPT teacher head0.363
Teacher spread0.305 · 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

Citations47
Published2018
Admission routes1
Has abstractyes

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