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Record W2758508335 · doi:10.1159/000479689

Anogenital Distance in Term Newborns in Kumasi, Ghana

2017· article· en· W2758508335 on OpenAlexaff
Serwah Bonsu Asafo‐Agyei, Emmanuel Ameyaw, Jean‐Pierre Chanoine, Margaret Zacharin, Samuel Blay Nguah, O O Jarrett

Bibliographic record

VenueHormone Research in Paediatrics · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSexual Differentiation and Disorders
Canadian institutionsBC Children's HospitalUniversity of British Columbia
Fundersnot available
KeywordsAnogenital distanceAnusMedicinePenisScrotumAnthropometryClitorisPerineumGynecologyAnatomyInternal medicinePregnancyBiologyFetusIn utero

Abstract

fetched live from OpenAlex

BACKGROUND: Anogenital distance (AGD) is a simple noninvasive measure of foetal androgen exposure. This study was done to generate normative data on AGD in Ghanaian newborns. METHODS: AGD was measured in 644 male and 612 female term newborns; including the distance between the anterior base of the penis and the centre of the anus, the posterior base of the penis and the centre of the anus, and the posterior base of the scrotum and the centre of the anus (ASD) in males and the distance from the anus to the fourchette (AF) and from the anus to the base of the clitoris in females. Other anthropometric and parental socio-demographic indices were also documented. RESULTS: AGD was sexually dimorphic; with a mean ± SD ASD and AF of 25.5 ± 5.1 and 13.6 ± 2.7 mm, respectively. There was a significant correlation between AGD and birth weight, birth length, and occipitofrontal circumference (p < 0.05). ASD was significantly longer (p < 0.001) in newborns (83/644; 12.9%) of mothers who had ingested herbs during pregnancy. CONCLUSION: AGD was approximately twice as long in males compared to females and can serve as a useful indicator of androgen exposure. Measurements of AGD also need to factor in anthropometric parameters, which are important correlates of AGD.

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)0.001
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 score0.024
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.061
GPT teacher head0.375
Teacher spread0.314 · 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
Published2017
Admission routes1
Has abstractyes

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