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Record W2979726525 · doi:10.5206/uwomj.v88i1.6518

Maternal pre-pregnancy body mass index and offspring temperament at 3 months

2019· article· en· W2979726525 on OpenAlexaffvenueabout
Taylor M. Mehta, John E. Krzeczkowski, Ryan J. Van Lieshout

Bibliographic record

VenueUniversity of Western Ontario Medical Journal · 2019
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsTemperamentNegative affectivityOffspringPregnancyBody mass indexConfoundingExtraversion and introversionMedicinePsychologyObesityObstetricsPositive affectivityMass indexPersonalityClinical psychologyDevelopmental psychologyEndocrinologyInternal medicineBiologyBig Five personality traits

Abstract

fetched live from OpenAlex

Introduction: Pre-pregnancy obesity has been linked to emotional and behavioural problems in offspring, though it remains unclear when the presence of these difficulties first emerges. Method: We examined the association between maternal pre-pregnancy body mass index (BMI) and temperament at 3 months of age in the offspring of 16 women residing in Hamilton, Ontario. Infant temperament was measured using the Infant Behaviour Questionnaire Revised, which specifically examined surgency/extraversion, negative affectivity, and orienting/regulation. Results: A statistically significant association was observed between maternal BMI and infant negative affectivity (B=0.05, 95% CI=0.01-0.08), which remained significant after adjusting for confounding variables (B=0.04, 95% CI=0.01-0.08). Conclusion: The current study provides evidence that fetal exposure to high maternal BMI during pregnancy is associated with increased negative affectivity in infants at 3 months of age. The results suggest that the intrauterine environment associated with high maternal BMI may influence temperament at a very early stage in development.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.209

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0020.000

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 head0.007
GPT teacher head0.224
Teacher spread0.217 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2019
Admission routes3
Has abstractyes

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