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Record W2622274844 · doi:10.1186/s13633-017-0045-y

Clitoral size in term newborns in Kumasi, Ghana

2017· article· en· W2622274844 on OpenAlexaff
Serwah Bonsu Asafo‐Agyei, Emmanuel Ameyaw, Jean‐Pierre Chanoine, Margaret Zacharin, Samuel Blay Nguah

Bibliographic record

VenueInternational Journal of Pediatric Endocrinology · 2017
Typearticle
Languageen
FieldMedicine
TopicFemale Genital Mutilation/Cutting Issues
Canadian institutionsBC Children's HospitalUniversity of British Columbia
FundersEuropean Society for Paediatric Endocrinology
KeywordsMedicineTerm (time)Pediatrics

Abstract

fetched live from OpenAlex

Data on normative clitoral sizes in newborns is relatively sparse and racial/ethnic differences have also been reported. This study was performed to establish norms for clitoral size in term Ghanaian female newborns. This was a cross-sectional study of all apparently well full-term newborns of postnatal age < 48 h and birth weight between 2.5 and 4.0 kg delivered at Komfo Anokye Teaching Hospital between May and September, 2014. Anthropometric and genital parameters were documented for study subjects as well as parental socio-demographic indices. In 612 newborn females studied, the mean (±SD) clitoral length (MCL) and the mean (±SD) clitoral width (MCW) were 4.13 ± 1.6 mm and 4.21 ± 1.1 mm, respectively. MCL was inversely related to birth weight (r = −0.62; p < 0.001) while MCW was inversely related to both gestational age (r = −0.1; p = 0.02) and birth weight (r = −0.54; p < 0.001). Babies with a clitoris that was completely covered by the labia majora had relatively lower clitoral sizes (p < 0.001) than those who had a partially covered or prominent clitoris. Neither MCL nor MCW differed significantly by birth length or maternal tribe. Clitoral size varies with birth weight and gestational age. Babies with a completely covered clitoris are unlikely to warrant detailed clitoral measurements for clitoromegaly.

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)0.002
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.361
Teacher spread0.329 · 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

Citations17
Published2017
Admission routes1
Has abstractyes

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