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Record W2273866904 · doi:10.1093/nutrit/nuv103

Role of maternal vitamins in programming health and chronic disease

2016· review· en· W2273866904 on OpenAlexafffund
Emanuela Pannia, Clara E. Cho, Ruslan Kubant, Diana Sánchez‐Hernández, Pedro S.P. Huot, G. Harvey Anderson

Bibliographic record

VenueNutrition Reviews · 2016
Typereview
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsUniversity of Toronto
FundersInstitute of Nutrition, Metabolism and DiabetesNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsOffspringPregnancyVitaminPhysiologyGestationMedicineDiseaseEnvironmental healthBiologyEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

Vitamin consumption prior to and during pregnancy has increased as a result of proactive recommendations by health professionals, wide availability of vitamin supplements, and liberal food-fortification policies. Folic acid, alone or in combination with other B vitamins, is the most recommended vitamin consumed during pregnancy because deficiency of this vitamin leads to birth defects in the infant. Folic acid and other B vitamins are also integral components of biochemical processes that are essential to the development of regulatory systems that control the ability of the offspring to adapt to the external environment. Although few human studies have investigated the lasting effects of high vitamin intakes during pregnancy, animal models have shown that excess vitamin supplementation during gestation is associated with negative metabolic effects in both the mothers and their offspring. This research from animal models, combined with the recognition that epigenetic regulation of gene expression is plastic, provides evidence for further examination of these relationships in the later life of pregnant women and their children.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.735
Threshold uncertainty score0.761

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.387
Teacher spread0.329 · 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 teacher head, 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

Citations37
Published2016
Admission routes2
Has abstractyes

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