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Record W2061704889 · doi:10.3109/14767050903551491

How does maternal obesity affect the routine fetal anatomic ultrasound?

2010· article· en· W2061704889 on OpenAlexaff
Cynthia Maxwell, Elizabeth Dunn, George Tomlinson, Phyllis Glanc

Bibliographic record

VenueThe Journal of Maternal-Fetal & Neonatal Medicine · 2010
Typearticle
Languageen
FieldMedicine
TopicGestational Diabetes Research and Management
Canadian institutionsMount Sinai HospitalPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsAffect (linguistics)UltrasoundMedicineObstetricsObesityFetusPregnancyPsychologyInternal medicineRadiologyBiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the completion rate for the routine anatomic survey in obese pregnant women with body mass index (BMI)≥30 as compared to normal weight controls (BMI: 20-25). METHODS: A retrospective analysis of the routine anatomic survey was performed in 100 consecutive women with a BMI≥30. Each subject was matched to two normal weight controls, controlling for gestational age. Exclusion criteria such as anatomic abnormalities or multiple gestations were known. The degree of visibility (satisfactory, moderate or unsatisfactory), indication for repeat examination and placental location were assessed. RESULTS: Average BMI in the index cases was 35.7 (range: 30-64.8). Twenty-six (26%) of index cases were considered incomplete as compared to 5 (2.5%) of the 200 controls. The anatomic survey was completed in 74 (74%) of index cases compared with 195 (97.5%) of controls. Visibility was satisfactory in 28 (28%) of index cases, moderate in 46 (46%) and unsatisfactory in 26 (26%). In comparison, 177 (88.5%) were satisfactory, 17 (8.5%) moderate and 6 (3%) were poor in controls. CONCLUSIONS: The completion rate for the routine anatomic survey in obese (BMI≥30) pregnant women was significantly lower as compared to normal weight pregnant women.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.639
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.265
Teacher spread0.258 · 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

Citations35
Published2010
Admission routes1
Has abstractyes

Explore more

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