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Record W2017545725 · doi:10.3390/ijerph110808166

The Association between Season of Pregnancy and Birth-Sex among Chinese

2014· article· en· W2017545725 on OpenAlexaff
Tan Xu, Dongdong Lin, Hui Liang, Mei Chen, Weijun Tong, Yongping Mu, Cindy Feng, Yongqing Gao, Yumei Zheng, Wenjie Sun

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicDemographic Trends and Gender Preferences
Canadian institutionsUniversity of Saskatchewan
FundersFogarty International CenterNational Institutes of Health
KeywordsAssociation (psychology)PregnancySeason of birthDemographyMedicinePsychologyBiologyGeneticsSociology

Abstract

fetched live from OpenAlex

OBJECTIVE: although numerous studies have reported the association between birth season and sex ratio, few studies have been conducted in subtropical regions in a non-Western setting. The present study assessed the effects of pregnancy season on birth sex ratio in China. METHODS: We conducted a national population-based retrospective study from 2006-2008 with 3175 children-parents pairs enrolled in the Northeast regions of China. Demographics and data relating to pregnancy and birth were collected and analyzed. A multiple logistical regression model was fitted to estimate the regression coefficient and 95% confidence interval (CI) of refractive error for mother pregnancy season, adjusting for potential confounders. RESULTS: After adjusting for parental age (cut-off point was 30 years), region, nationality, mother education level, and mother miscarriage history, there is a significant statistical different mother pregnancy season on birth-sex. Compared with mothers who were pregnant in spring, those pregnant in summer or winter had a high probability of delivering girls (p < 0.05). The birth-sex ratio varied with months. CONCLUSIONS: Our results suggested that mothers pregnant in summer and winter were more likely to deliver girls, compared with those pregnant in spring. Pregnancy season may play an important role in the birth-sex.

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.257
Threshold uncertainty score0.293

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
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)0.0000.000

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 head0.056
GPT teacher head0.382
Teacher spread0.327 · 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 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

Citations6
Published2014
Admission routes1
Has abstractyes

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