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Pre‐pregnancy and pregnancy obesity and neurodevelopmental outcomes in offspring: a systematic review

2011· review· en· W1576494209 on OpenAlexafffund
Ryan J. Van Lieshout, Valerie H. Taylor, M. H. Boyle

Bibliographic record

VenueObesity Reviews · 2011
Typereview
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsOffspringPregnancyObesityMedicineOverweightPsychiatryPediatricsEndocrinology

Abstract

fetched live from OpenAlex

Maternal obesity in pregnancy is associated with a number of adverse outcomes for mother and her offspring both perinatally and later in life. This includes recent evidence that suggests that obesity in pregnancy may be associated with central nervous system problems in the foetus and newborn. Here, we systematically review studies that have explored associations between maternal overweight and obesity in pregnancy and cognitive, behavioural and emotional problems in offspring. The 12 studies eligible for this review examined a wide range of outcomes across the lifespan and eight provided evidence of a link. These data suggest that the offspring of obese pregnancies may be at increased risk of cognitive problems and symptoms of attention deficit hyperactivity disorder in childhood, eating disorders in adolescence and psychotic disorders in adulthood. Given the limitations of existing data, these findings warrant further study, particularly in light of the current worldwide obesity epidemic.

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)0.002
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0050.007
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.074
GPT teacher head0.347
Teacher spread0.273 · 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 designSystematic review
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

Citations177
Published2011
Admission routes2
Has abstractyes

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