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Record W3006268264 · doi:10.23937/2474-1353/1510110

Pre-Twin Screen - A Multi-Disciplinary Approach for a Personalized Prenatal Diagnostics and Care for Twin Pregnancies

2020· article· en· W3006268264 on OpenAlexaff
Hamutal Meiri, Nadav Kugler, Ran Svirsky, Oliver Kagan, Brown Richard Nicolas, Miron Piere, Borrell Antoni, Anna Goncé, M. Bennásar, Geipel Annegret, Brigitte Strizek, Syngeleki Argyro, Nicolaides Kypros, Howard Cuckle, Ron Maymon

Bibliographic record

VenueInternational Journal of Women s Health and Wellness · 2020
Typearticle
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsMcGill University
Fundersnot available
KeywordsObstetricsTwin PregnancyPreeclampsiaIntrauterine growth restrictionMedicineGestational diabetesPregnancyFetal growthAdvanced maternal ageFetusGestationBiologyGenetics

Abstract

fetched live from OpenAlex

The prevalence of twin pregnancies is rising globally due to increased assisted conception and advanced maternal age in pregnancy. Twin pregnancies have 5-9 times higher frequencies of fetal chromosomal and structural abnormalities, often deliver preterm, and have high prevalence of gestational diabetes mellitus (GDM), preeclampsia (PE), and intrauterine growth restriction (IUGR) compared to singletons.

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)0.000
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score0.451

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.034
GPT teacher head0.333
Teacher spread0.299 · 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 designQualitative
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

Citations3
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Women s Health and WellnessSame topicAssisted Reproductive Technology and Twin PregnancyFrench-language works237,207