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Record W1964784030 · doi:10.1139/h06-001

Nutrition for healthy pregnancy outcomes

2006· review· en· W1964784030 on OpenAlexaffvenue
Tannys D.R. Vause, Pat Martz, F Richard, Leah Gramlich

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2006
Typereview
Languageen
FieldMedicine
TopicBirth, Development, and Health
Canadian institutionsRoyal Alexandra HospitalUniversity of Alberta
Fundersnot available
KeywordsWeight gainPregnancyOffspringMedicineObesityObstetricsGestational diabetesPediatricsGestationBody weightEndocrinology

Abstract

fetched live from OpenAlex

Many healthcare professionals and their patients are aware of the importance of proper nutrition during pregnancy, but may not be aware of specific nutritional recommendations on how to achieve a healthy pregnancy outcome. This review article aims to discuss the implications maternal nutritional status and weight gain have in both the short and long terms. Babies born to mothers with inadequate weight gain are more likely to be premature and small for gestational age (SGA). They are also predisposed to obesity and metabolic problems later in life. Women with excessive weight gain during pregnancy are at increased risk for developing type II diabetes later in life. Their offspring also have increased body fat as babies and during childhood. Pregnant women need to be informed about appropriate weight gain and how to achieve this, and should be given specific nutritional recommendations and weight-gain goals.

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)0.001
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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.002

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 head0.053
GPT teacher head0.359
Teacher spread0.306 · 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

Citations17
Published2006
Admission routes2
Has abstractyes

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